[365] Yu Zhao, Shan Xiong, Qin Ren, Min Li, Jun Wang, Lin Yang, Di Wu, Kejing Tang, Xiaojie Pan, Fengxia Chen, Wenxiang Wang, Shi Jin, Xianling Liu, Gen Lin, Wenxiu Yao, Linbo Cai, Yi Yang, Jixian Liu, Jingxun Wu, Wenfan Fu, Kai Sun, Feng Li, Bo Cheng, Shuting Zhan, Haixuan Wang, Ziwen Yu, Xiwen Liu, Ran Zhong, Huiting Wang, Ping He, Yongmei Zheng, Peng Liang, Longfei Chen, Ting Hou, Junzhou Huang, Bing He, Jiangning Song, Lin Wu, Chengping Hu, Jianxing He, Jianhua Yao and Wenhua Liang, "Deep Multiple Instance Learning-enabled Gene Mutation Prediction of Lung Cancer from Histopathology Images: a Multicentre Retrospective Study", The Lancet Oncology, To Appear.

[364] De Cai, Jie Chen, Junhan Zhao, Yuan Xue, Sen Yang, Wei Yuan, Min Feng, Haiyan Weng, Shuguang Liu, Yulong Peng, Junyou Zhu, Kanran Wang, Christopher Jackson, Hongping Tang, Junzhou Huang and Xiyue Wang, "HiCervix: An Extensive Hierarchical Dataset and Benchmark for Cervical Cytology Classification", IEEE Transactions on Medical Imaging, To Appear.

[363] Mingcai Chen, Yu Zhao, Bing He, Zongbo Han, Junzhou Huang, Bingzhe Wu and Jianhua Yao, "Learning with Noisy Labels over Imbalanced Subpopulations", IEEE Transactions on Neural Networks and Learning Systems, To Appear.

[362] Jiaqi Han, Wenbing Huang, Yu Rong, Tingyang Xu, Fuchun Sun and Junzhou Huang, "Structure-Aware DropEdge Towards Deep Graph Convolutional Networks". IEEE Transactions on Neural Networks and Learning Systems, To Appear.

[361] Kaili Ma, Han Yang, Shanchao Yang, Kangfei Zhao, Lanqing Li, Yongqiang Chen, Junzhou Huang, James Cheng and Yu Rong, “Solving the Non-Submodular Network Collapse Problems via Decision Transformer”, Neural Networks, Volume 176, August 2024.

[360] Feng Jiang, Yuzhi Guo, Hehuan Ma, Saiyang Na, Wenliang Zhong, Yi Han, Tao Wang and Junzhou Huang, "GTE: A Graph Learning Framework for Prediction of T-Cell Receptors and Epitopes Binding Specificity", Briefings in Bioinformatics, Volume 25, Issue 4, July 2024.

[359] Qifeng Bai, Tingyang Xu, Junzhou Huang and Horacio Prez-Snchez, "Geometric Deep Learning Methods and Applications in 3D Structure-based Drug Design", Drug Discovery Today, Volume 29, Issue 7, July 2024.

[358] Weizhi An, Yuzhi Guo, Yatao Bian, Hehuan Ma, Jinyu Yang, Chunyuan Li and Junzhou Huang, "Advancing DNA Language Models through Motif-Oriented Pre-training with MoDNA", Biomedinformatics, Volume 4, Number 2, pp.1556-1571, June 2024.

[357] Jiahan Liu, Chaochao Yan, Chan Lu, Junzhou Huang, Le Ou-Yang and Peilin Zhao, "MARS: A Motif-based Autoregressive Model for Retrosynthesis Prediction", Bioinformatics, Volume 40, Issue 3, March 2024.

[356] Hehuan Ma, Feng Jiang, Yuzhi Guo and Junzhou Huang, "Towards Robust Self-training for Molecular Biology Prediction Tasks, Journal of Computational Biology, Volume 31, Issue 3, pp. 213-228, March 2024.

[355] Junchi Yu, Tingyang Xu, Yu Rong, Yatao Bian, Junzhou Huang and Ran He, "Recognizing Predictive Substructures with Subgraph Information Bottleneck", IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 46, pp. 1650-1663, March 2024.

[354] Peng Xia, Ze Chen, Juanxi Tian, Yangrui Gong, Ruibo Hou, Yue Xu, Zhenbang Wu, Zhiyuan Fan, Yiyang Zhou, Kangyu Zhu, Wenhao Zheng, Zhaoyang Wang, Xiao Wang, Xuchao Zhang, Chetan Bansal, Marc Niethammer, Junzhou Huang, Hongtu Zhu, Yun Li, Jimeng Sun, Zongyuan Ge, Gang Li, James Zou and Huaxiu Yao, "CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models", In Proc. of the 38th Annual Conference on Neural Information Processing Systems, NeurIPS'24, Vancouver, Canada, December 2024.

[353] Feng Jiang, Yuzhi Guo, Hehuan Ma, Saiyang Na, Weizhi An, Bing Song, Yi Han, Jean Gao, Tao Wang and Junzhou Huang, "AlphaEpi: Enhancing B Cell Epitope Prediction with AlphaFold 3", In Proc. of the 15th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, ACM BCB'24, Shenzhen, China, November 2024.

[352] Thao M. Dang, Yuzhi Guo, Hehuan Ma, Qifeng Zhou, Saiyang Na, Jean Gao and Junzhou Huang, "MFMF: Multiple Foundation Model Fusion Networks for Whole Slide Image Classification", In Proc. of the 15th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, ACM BCB'24, Shenzhen, China, November 2024.

[351] Jie Tan, Yu Rong, Kangfei Zhao, Tian Bian, Tingyang Xu, Junzhou Huang, Hong Cheng and Helen Meng, "Natural Language-Assisted Multi-modal Medication Recommendation", In Proc. of the 33rd ACM International Conference on Information and Knowledge Management, CIKM’24, Boise, Idaho, USA, October 2024.

[350] Tian Bian, Yifan Niu, Heng Chang, Divin Yan, Junzhou Huang, Yu Rong, Tingyang Xu, Jia Li, Hong Cheng, "Hierarchical Graph Latent Diffusion Model for Conditional Molecule Generation", In Proc. of the 33rd ACM International Conference on Information and Knowledge Management, CIKM’24, Boise, Idaho, USA, October 2024.

[349] Weizhi An, Wenliang Zhong, Feng Jiang, Hehuan Ma and Junzhou Huang, "Causal Subgraphs and Information Bottlenecks: Redefining OOD Robustness in Graph Neural Networks", In Proc. of the 18th European Conference on Computer Vision, ECCV'24, Milan, Italy, October 2024.

[348] Qifeng Zhou, Wenliang Zhong, Yuzhi Guo, Michael Xiao, Hehuan Ma and Junzhou Huang, "PathM3: A Multimodal Multi-Task Multiple Instance Learning Framework for Whole Slide Image Classification and Captioning", In Proc. of the 27th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI’24, Marrakesh, Morocco, October 2024.

[347] Wenliang Zhong, Wenyi Wu, Qi Li, Boxin Du, Karim Bouyarmane, Shioulin Sam, Ismail Tutar and Junzhou Huang, "Enhancing Multimodal Large Language Models with Multi-instance Visual Prompt Generator for Visual Representation Enrichment”, SIGIR 2024 Workshop on Multimodal Representation and Retrieval, MRR’24, Washington DC, July 2024.

[346] Peng Xia, Ze Chen, Juanxi Tian, Gong Yangrui, Ruibo Hou, Yue Xu, Zhenbang Wu, Zhiyuan Fan, Yiyang Zhou, Kangyu Zhu, Wenhao Zheng, Zhaoyang Wang, Xiao Wang, Xuchao Zhang, Chetan Bansal, Marc Niethammer, Junzhou Huang, Hongtu Zhu, Yun Li, Jimeng Sun, Zongyuan Ge, Gang Li, James Zou, Huaxiu Yao, "CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models", ICML 2024 Workshop on Foundation Models in the Wild, Vienna, Austria, July 2024.

[345] Qichuan Yin, Junzhou Huang, Huaxiu Yao, and Linjun Zhang, “Distribution-Free Fair Federated Learning with Small Samples”, The AAAI Workshop on Artificial Intelligence with Biased or Scarce Data, Vancouver, Canada, February 2024.

[344] Wenyi Wu, Qi Li, Wenliang Zhong and Junzhou Huang, "MIVC: Multiple Instance Visual Component for Visual-Language Models", In Proc. of IEEE/CVF Winter Conference on Applications of Computer Vision, WACV'24, Waikoloa, Hawaii, USA, January 2024.

2023

[343] Shiwei Zhou, Jinyu Yang, Krishna Konduri, Junzhou Huang, Lifeng Yu and Mingwu Jin, "Spatiotemporal Denoising of Low-dose Cardiac CT Image Sequences using RecycleGAN", Biomedical Physics & Engineering Express, Volume 9, September 2023.

[342] Yuwei Miao, Hehuan Ma and Junzhou Huang, "Recent Advances in Toxicity Prediction: Applications of Deep Graph Learning", Chemical Research in Toxicology, Volume 36, pp. 1206-1226, August 2023.

[341] Xuefeng Du, Tian Bian, Yu Rong, Bo Han, Tongliang Liu, Tingyang Xu, Wenbing Huang, Yixuan Li and Junzhou Huang, "Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions", Transactions on Machine Learning Research, June 2023.

[340] Heng Chang, Yu Rong, Tingyang Xu, Wenbing Huang, Honglei Zhang, Peng Cui, Xin Wang, Wenwu Zhu and Junzhou Huang, "Adversarial Attack Framework on Graph Embedding Models with Limited Knowledge", IEEE Transactions on Knowledge and Data Engineering, Volume 35, Issue 5, pp. 4499-4513, May 2023.

[339] Xiyue Wang, Jun Zhang, Sen Yang, Jingxi Xiang, Feng Luo, Minghui Wang, Jing Zhang, Wei Yang, Junzhou Huang and Xiao Han, "A Generalizable and Robust Deep Learning Algorithm for Mitosis Detection in Multicenter Breast Histopathological Images", Medical Image Analysis, Volume 84, February 2023.

[338] Mohammad Minhazul Haq, Hehuan Ma and Junzhou Huang, "NuSegDA: Domain Adaptation for Nuclei Segmentation", Frontiers in Big Data-Medicine and Public Health, Volume 6, February 2023.

[337] Wenhua Zhang, Jun Zhang, Xiyue Wang, Sen Yang, Junzhou Huang, Wei Yang, Wenping Wang and Xiao Han, "Merging Nucleus Datasets by Correlation-based Cross-Training", Medical Image Analysis, Volume 84, February 2023.

[336] Kangfei Zhao, Zhiwei Zhang, Yu Rong, Jeffrey Yu and Junzhou Huang, "Finding Critical Users in Social Communities via Graph Convolutions", IEEE Transactions on Knowledge and Data Engineering, Volume 35, Issue 1, pp. 456-468, January 2023.

[335] Zhen Peng, Minnan Luo, Wenbing Huang, Jundong Li, Qinghua Zheng, Fuchun Sun and Junzhou Huang, "Learning Representations by Graphical Mutual Information Estimation and Maximization", IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 45, Issue 1, pp. 722-737, January 2023.

[334] Xiyue Wang, Yuexi Du, Sen Yang, Jun Zhang, Minghui Wang, Jing Zhang, Wei Yang, Junzhou Huang and Xiao Han, "RetCCL: Clustering-guided Contrastive Learning for Whole-slide Image Retrieval", Medical Image Analysis, Volume 83, January 2023.

[333] Long-Kai Huang, Peilin Zhao, Junzhou Huang and Sinno Pan, "Retaining Beneficial Information from Detrimental Data for Neural Network Repair", In Proc. of the 36th Annual Conference on Neural Information Processing Systems, NeurIPS'23, New Orleans, Louisiana, USA, December 2023.

[332] Yucheng Shi, Hehuan Ma, Wenliang Zhong, Qiaoyu Tan, Gengchen Mai, Xiang Li, Tianming Liu and Junzhou Huang, "ChatGraph: Interpretable Text Classification by Converting ChatGPT Knowledge to Graphs", IEEE International Conference on Data Mining Workshops on Learning with Knowledge Graphs: Opportunities and Challenges with ChatGPT, Shanghai, China, December 2023.

[331] Lu Zhang, Saiyang Na, Dajiang Zhu and Junzhou Huang, "Multimodal Deep Fusion in Hyperbolic Space for Mild Cognitive Impairment Study", In Proc. of the 26th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'23, Vancouver, Canada, October 2023.

[330] Qin Ren, Yu Zhao, Bing He, Bingzhe Wu, Sijie Mai, Fan Xu, Yueshan Huang, Yonghong He, Junzhou Huang and Jianhua Yao, "IIB-MIL: Integrated Instance-level and Bag-level Multiple Instances Learning with Label Disambiguation for Pathological Image Analysis", In Proc. of the 26th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'23, Vancouver, Canada, October 2023.

[329] Songhui Diao, Wenxue Zhou, Chenchen Qin, Jun Liao, Junzhou Huang, Wenming Yang and Jianhua Yao, "An Unsupervised Multispectral Image Registration Network for Skin Diseases", In Proc. of the 26th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'23, Vancouver, Canada, October 2023.

[328] Boxin Du, Rob Barton, Grant Galloway, Junzhou Huang, Ismail Tutar and Changhe Yuan, "Enhancing Catalog Relationship Problems with Heterogeneous Graphs and Graph Neural Networks Distillation", In Proc. of the 32th ACM International Conference on Information and Knowledge Management, CIKM'23, Birmingham, United Kingdom, October 2023.

[327] Wenliang Zhong, Hehuan Ma, Yu Rong, Yatao Bian, Long-Kai Huang, Yuzhi Guo, Peilin Zhao and Junzhou Huang, "CoSSL: A Context-based Semi-Supervised Framework for Molecular Property Prediction", ICML Workshop on Computational Biology, Honolulu, Hawaii, USA, July 2023.

[326] Yong Guo, Yaofo Chen, Yin Zheng, Qi Chen, Peilin Zhao, Junzhou Huang, Jian Chen, Mingkui Tan, "Pareto-Aware Neural Architecture Generation for Diverse Computational Budgets", IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, Vancouver, Canada, June 2023.

[325] Hanwen Liu, Peilin Zhao, Tingyang Xu, Yatao Bian, Junzhou Huang, Yuesheng Zhu and Yadong Mu, "Curriculum Graph Poisoning", In Proc. of the International World Wide Web Conference, WWW'23, Austin, Texas, USA, May 2023.

[324] Yifan Zhang, Peilin Zhao, Qingyao Wu, Bin Li, Junzhou Huang and Mingkui Tan, "Cost-Sensitive Portfolio Selection via Deep Reinforcement Learning", In Proc. of the 39th IEEE International Conference on Data Engineering, ICDE'23, Anaheim, California, USA, April 2023.

[323] Yuanfeng Ji, Lu Zhang, Jiaxiang Wu, Bingzhe Wu, Lanqing Li, Long-Kai Huang, Tingyang Xu, Yu Rong, Jie Ren, Ding Xue, Houtim Lai, Wei Liu, Junzhou Huang, Shuigeng Zhou, Ping Luo, Peilin Zhao and Yatao Bian,"DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-aided Drug Discovery - A Focus on Affinity Prediction Problems with Noise Annotations", In Proc. of the 37th AAAI Conference on Artificial Intelligence, AAAI’23, Washington, DC, USA, February 2023.

[322] Jinyu Yang, Jingjing Liu, Ning Xu and Junzhou Huang, "TVT: Transferable Vision Transformer for Unsupervised Domain Adaptation", IEEE Winter Conference on Applications of Computer Vision, WACV’23, Waikoloa, Hawaii, USA, January 2023.

[321] Junzhou Huang and Ruoyu Li, "Adaptive Graph Convolutional Neural Network and Its Biomedical Applications", State of the Art in Neural Networks and Their Applications, Volume 2, ISBN: 9780128198728, Elsevier, January 2023.

2022

[320] Wenhua Zhang, Jun Zhang, Sen Yang, Xiyue Wang, Wei Yang, Junzhou Huang, Wenping Wang and Xiao Han, "Knowledge-Based Representation Learning for Nucleus Instance Classification from Histopathological Images", IEEE Transactions on Medical Imaging, Volume 41, Issue 12, pp. 3939-3951, December 2022.

[319] Sen Yang, Tao Shen, Yuqi Fang, Xiyue Wang, Jun Zhang, Wei Yang, Junzhou Huang and Xiao Han, "DeepNoise: Signal and Noise Disentanglement based on Classifying Fluorescent Microscopy Images via Deep Learning", Genomics, Proteomics & Bioinformatics, Volume 20, Issue 5, pp. 989-1001, October 2022.

[318] Yong Guo, Yin Zheng, Mingkui Tan, Qi Chen, Zhipeng Li, Jian Chen, Peilin Zhao and Junzhou Huang, “Towards Accurate and Compact Architectures via Neural Architecture Transformer”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume: 44, Issue: 10, pp. 6501-6516, October 2022.

[317] Runhao Zeng, Wenbing Huang, Mingkui Tan, Yu Rong, Peilin Zhao, Junzhou Huang and Chuang Gan, "Graph Convolutional Module for Temporal Action Localization in Videos", IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume: 44, Issue 10, pp.6209-6223, October 2022.

[316] Lu Wang, Lei Han, Xinru Chen, Chengchang Li, Junzhou Huang, Weinan Zhang, Wei Zhang, Xiaofeng He and Dijun Luo, "Hierachical Multi-Agent Reinforcement Learning for Allocating Guaranteed Display Ads”, IEEE Transactions on Neural Networks and Learning Systems, Volume 33, Issu 10, pp. 5361-5373, October 2022

[315] Xiyue Wang, Sen Yang, Jun Zhang, Minghui Wang, Jing Zhang, Wei Yang, Junzhou Huang and Xiao Han, “Transformer-based Unsupervised Contrastive Learning for Histopathological Image Classification”, Medical Image Analysis, Volume 81, October 2022.

[314] Fan Yang, Wenchuan Wang, Fang Wang, Yuan Fang, Duyu Tang, Junzhou Huang, Hui Lu and Jianhua Yao, "scBERT as a Large-scale Pretrained Deep Language Model for Cell Type Annotation of Single-cell RNA-seq Data", Nature Machine Intelligence, Volume 4, pp. 852- 866, September 2022.

[313] Chaochao Yan, Peilin Zhao, Chan Lu, Yang Yu and Junzhou Huang, "RetroComposer: Composing Templates for Template-based Retrosynthesis Prediction", Biomolecules, Volume 12, September 2022.

[312] Piumi Sandarenu, Ewan KA Millar, Yang Song, Lois H Browne, Julia Beretov, Jodi Lynch, Peter Graham, Jitendra Jonnagaddala, Nick Hawkins, Junzhou Huang and Erik Meijering, "Survival Prediction in Triple Negative Breast Cancer Using Multiple Instance Learning of Histopathological Images", Scientific Reports, Volume 12, August 2022.

[311] Chaochao Yan, Jinyu Yang, Hehuan Ma and Junzhou Huang, "Molecule Sequence Generation with Rebalanced Variational Loss", Journal of Computational Biology, Volume 29, August 2022.

[310] Jing Liu, Bohan Zhuang, Zhuangwei Zhuang, Yong Guo, Junzhou Huang, Jinhui Zhu and Mingkui Tan, "Discrimination-aware Channel Pruning for Deep Model Compression", IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume: 44, Issue: 8, pp. 4035-4051, August 2022.

[309] Darshana Narayanan, Daniel Takahashi, Lauren Kelly, Sabina Hlavaty, Junzhou Huang and Asif Ghazanfar, "Prenatal Development of Neonatal Vocalizations", Elife, 11:e78485, July 2022.

[308] Xiaochu Tong, Dingyan Wang, Xiaoyu Ding, Xiaoqin Tan, Qun Ren, Geng Chen, Yu Rong, Tingyang Xu, Junzhou Huang, Hualiang Jiang, Mingyue Zheng and Xutong Li, “Blood-Brain Barrier Penetration Prediction Enhanced by Uncertainty Estimation”, Journal of Cheminformatics, Volume 14, Number 44, July 2022.

[307] Qifeng Bai, Shuo Liu, Yanan Tian, Tingyang Xu, Antonio Jesús Banegas-Luna, Horacio Pérez-Sánchez, Junzhou Huang, Huanxiang Liu and Xiaojun Yao, "Application Advances of Deep Learning Methods for De Novo Drug Design and Molecular Dynamics Simulation", WIREs Computational Molecular Science, Volume 12, Issue 3, June 2022.

[306] Xiaoying Lou, Niyun Zhou, Lili Feng, Zhenhui Li, Yuqi Fang, Xinjuan Fan, Yihong Ling, Hailing Liu, Xuan Zou, Jing Wang, Junzhou Huang, Jingping Yun, Jianhua Yao and Yan Huang, "Deep Learning Model for Predicting the Pathological Complete Response to Neoadjuvant Chemoradiotherapy of Locally Advanced Rectal Cancer", Frontiers in Oncology, June 2022.

[305] Yuzhi Guo, Jiaxiang Wu, Hehuan Ma, Sheng Wang and Junzhou Huang, "Deep Ensemble Learning with Atrous Spatial Pyramid Networks for Protein Secondary Structure Prediction", Biomolecules, 12, 774, June 2022.

[304] Junchi Yu, Tingyang Xu, Yu Rong, Junzhou Huang and Ran He, "Structure-aware Conditional Variational Auto-encoder for Constrained Molecule Optimization", Pattern Recognition, Volume 126, June 2022.

[303] Xiaohan Xing, Fan Yang, Hang Li, Jun Zhang, Yu Zhao, Mingxuan Gao, Junzhou Huang and Jianhua Yao, "Multi-Level Attention Graph Neural Network Based on Co-expression Gene Modules for Disease Diagnosis and Prognosis", Bioinformatics, Volume 38, Issue 8, pp. 2178-2186, April 2022.

[302] Hehuan Ma, Yatao Bian, Yu Rong, Wenbing Huang, Tingyang Xu, Weiyang Xie, Geyan Ye and Junzhou Huang, "Cross-Dependent Graph Neural Networks for Molecular Property Prediction", Bioinformatics, Volume 38, Issue 7, pp. 2003-2009, April 2022.

[301] Hailing Liu, Yu Zhao, Fan Yang, Xiaoying Lou, Feng Wu, Hang Li, Xiaohan Xing, Tingying Peng, Bjoern Menze, Junzhou Huang, Shujun Zhang, Anjia Han, Jianhua Yao and Xinjuan Fan, "Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer with Deep Learning", BME Frontiers, Volume 2022, pp. 1-12, March 2022.

[300] Jiezhang Cao, Yong Guo, Qingyao Wu, Chunhua Shen, Junzhou Huang and Mingkui Tan, "Improving Generative Adversarial Networks with Local Coordinate Coding", IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 44, Issue 1, pp. 211-227, January 2022.

[299] Junzhou Huang, Xinliang Zhu, Jiawen Yao,"Training a Deep Multiview Model Using Small Samples of Medical Data”, Artificial Intelligence in Cancer Diagnosis and Prognosis, Volume 1: Lung and Kidney Cancer, IOP Publishing, 2022.

[298] Hehuan Ma, Yu Rong and Junzhou Huang, "Graph Neural Networks: Scalability", Graph Neural Networks: Foundations, Frontiers, and Applications, Springer, 2022.

[297] Xiyue Wang, Jinxi Xiang, Jun Zhang, Sen Yang, Zhongyi Yang, Ming-Hui Wang, Jing Zhang, Yang Wei, Junzhou Huang, Xiao Han, "SCL-WC: Cross-Slide Contrastive Learning for Weakly-Supervised Whole-Slide Image Classification", In Proc. of the 36th Annual Conference on Neural Information Processing Systems, NeurIPS'22, New Orleans, Louisiana, USA, December 2022.

[296] Bingzhe Wu, Zhipeng Liang, Yuxuan Han, Yatao Bian, Peilin Zhao, Junzhou Huang and Chaochao Chen, "D3RF: Distributionally Robust Federated Drug Discovery with Inter-client Noise", The 1st International Workshop on Federated Learning with Graph Data at ACM CIKM, Atlanta, Georgia, United States, October 2022.

[295] Jiawei Yang, Hanbo Chen, Yuan Liang, Junzhou Huang, Lei He and Jianhua Yao, "ConCL: Concept Contrastive Learning for Dense Prediction Pre-training in Pathology Images", In Proc. of the 17th European Conference on Computer Vision, ECCV'22, Tel Aviv, Israel, October 2022.

[294] Mohammad Minhazul Haq and Junzhou Huang, "Self-Supervised Pre-Training for Nuclei Segmentation", In Proc. of the 25th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI’22, Singapore, September 2022.

[293] Yu Zhao, Zhenyu Lin, Kai Sun, Yidan Zhang, Junzhou Huang, Liansheng Wang and Jianhua Yao, "SETMIL: Spatial Encoding Transformer-based Multiple Instance Learning for Pathological Image Analysis", In Proc. of the 25th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI’22, Singapore, September 2022.

[292] Yuli Jiang, Yu Rong, Hong Cheng, Xin Huang, Kangfei Zhao and Junzhou Huang, "Query Driven-Graph Neural Networks for Community Search: From Non-Attributed, Attributed, to Interactive Attributed", In Proc. of the 48th International Conference on Very Large Data Bases, VLDB'22, Sydney, Australia, September 2022.

[291] Hehuan Ma, Feng Jiang, Yu Rong, Yuzhi Guo and Junzhou Huang, "Robust Self-training Strategy for Various Molecular Biology Prediction Tasks", In Proc. of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, ACM BCB’22, Chicago, Illinois, USA, August 2022.

[290] Weizhi An, Yuzhi Guo, Yatao Bian, Hehuan Ma, Jinyu Yang, Chunyuan Li and Junzhou Huang, "MoDNA: Motif-Oriented Pre-training for DNA Language Model", In Proc. of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, ACM BCB’22, Chicago, Illinois, USA, August 2022.

[289] Chunyuan Li, Xinliang Zhu, Jiawen Yao and Junzhou Huang, "Hierarchical Transformer for Survival Prediction Using Multi-modality Whole Slide Images and Genomics", In Proc. of the 26th International Conference on Pattern Recognition, ICPR’22, Montral Qubec, Canada, August 2022.

[288] Long-Kai Huang, Ying Wei, Yu Rong, Qiang Yang and Junzhou Huang, "Frustratingly Easy Transferability Estimation", In Proc. of the 39th International Conference on Machine Learning, ICML'22, Baltimore, Maryland, USA, July 2022.

[287] Songtao Liu, Rex Ying, Hanze Dong, Lanqing Li, Tingyang Xu, Yu Rong, Peilin Zhao, Junzhou Huang and Dinghao Wu, "Local Augmentation for Graph Neural Networks", In Proc. of the 39th International Conference on Machine Learning, ICML'22, Baltimore, Maryland, USA, July 2022.

[286] Erxue Min, Yu Rong, Tingyang Xu, Yatao Bian, Peilin Zhao, Luo Da, Kangyi Lin, Sophia Ananiadou and Junzhou Huang, "Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer", In Proc. of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'22, Madrid, Spain, July 2022

[285] Jinyu Yang, Jiali Duan, Son Tran, Yi Xu, Liqun Chen, Belinda Zeng, Trishul Chilimbi, Sampath Chanda and Junzhou Huang, "Vision-Language Pre-Training with Triple Contrastive Learning", In Proc. of IEEE Conference on Computer Vision and Pattern Recognition, CVPR'22, New Orleans, Louisiana, USA, June 2022.

[284] Yonghang Guan, Jun Zhang, Kuan Tian, Sen Yang, Pei Dong, Jinxi Xiang, Wei Yang, Junzhou Huang, Yuyao Zhang and Xiao Han, "Node-aligned Graph Convolutional Network for Whole-slide Image Representation and Classification", In Proc. of IEEE Conference on Computer Vision and Pattern Recognition, CVPR'22, New Orleans, Louisiana, USA, June 2022.

[283] Zongbo Han, Fan Yang, Junzhou Huang, Changqing Zhang and Jianhua Yao, "Multimodal Dynamics: Dynamical Fusion for Trustworthy Multimodal Classification", In Proc. of IEEE Conference on Computer Vision and Pattern Recognition, CVPR'22, New Orleans, Louisiana, USA, June 2022.

[282] Wenbing Huang, Jiaqi Han, Yu Rong, Tingyang Xu, Fuchun Sun and Junzhou Huang, "Constrained Graph Mechanics Networks", In Proc. of the Tenth International Conference on Learning Representations, ICLR'22, April 2022.

[281] Yatao Bian, Yu Rong, Tingyang Xu, Jiaxiang Wu, Andreas Krause and Junzhou Huang, "Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning", In Proc. of the Tenth International Conference on Learning Representations, ICLR'22, April 2022.

[280] Erxue Min, Yu Rong, Tingyang Xu, Yatao Bian, Peilin Zhao, Junzhou Huang and Sophia Ananiadou, "Divide-and-Conquer: Post-User Interaction Network for Fake News Detection on Social Media", In Proc. of International World Wide Web Conference, WWW’22, Lyon, France, April 2022.

[279] Yuzhi Guo, Jiaxiang Wu, Hehuan Ma and Junzhou Huang, "Self-supervised Pretraining for Protein Embeddings Using Tertiary Structures", In Proc. of the Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI'22, Vancouver, Canada, February 2022.

[278] Ashwin Raju, Shun Miao, Dakai Jin, Le Lu, Junzhou Huang, Adam Harrison, "Deep Implicit Statistical Shape Models for 3D Medical Image Delineation", In Proc. of the Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI'22, Vancouver, Canada, February 2022.

[277] Peng Han, Peilin Zhao, Chan Lu, Junzhou Huang, Jiaxiang Wu, Shuo Shang, Bin Yao, Xiangliang Zhang, "GNN-Retro: Retrosynthetic planning with Graph Neural Networks", In Proc. of the Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI'22, Vancouver, Canada, February 2022.

2021

[276] Tao Shen, Jiaxiang Wu, Haidong Lan, Liangzhen Zheng, Jianguo Pei, Sheng Wang, Wei Liu and Junzhou Huang, "When Homologous Sequences Meet Structural Decoys: Accurate Contact Prediction by tFold in CASP14", PROTEINS: Structure, Function, and Bioinformatics, Volume89, Issue12, pp. 1901-1910, December 2021.

[275] Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang, Yong Guo, Peilin Zhao, Junzhou Huang, Mingkui Tan, "Disturbance-immune Weight Sharing for Neural Architecture Search”, Neural Networks, Volume 144, pp. 553-564, December 2021.

[274] Kelong Mao, Xi Xiao, Tingyang Xu, Yu Rong, Junzhou Huang and Peilin Zhao, "Molecular Graph Enhanced Transformer for Retrosynthesis Prediction", Neurocomputing, Volume 457, pp. 193-202, October 2021.

[273] Yang Yu, Tingyang Xu, Jiawen Li, Yaping Qiu, Yu Rong, Zhen Gong, Xuemin Cheng, Liming Dong, Wei Liu, Jin Li, Dengfeng Dou and Junzhou Huang, "A Novel Scalarized Scaffold Hopping Algorithm with Graph-based Variational Autoencoder for Discovery of JAK1 Inhibitors", ACS Omega, Volume 6, pp. 22945-22954, August 2021.

[272] Meng Yue, Jun Zhang, Xinran Wang, Kezhou Yan, Lijing Cai, Kuan Tian, Shuyao Niu, Xiao Han, Yongqiang Yu, Junzhou Huang, Dandan Han, Jianhua Yao, Yueping Liu, "Can AI-assisted Microscope Facilitate Breast HER2 Interpretation? A Multi-institutional Ring Study”, Virchows Archiv, 479, pp. 443-449, July 2021.

[271] Qifeng Bai, Jian Ma, Shuo Liu, Tingyang Xud, Antonio Jess Banegas-Luna, Horacio Prez-Snchez, Yanan Tian, Junzhou Huang, Huanxiang Liu and Xiaojun Yao, "WADDAICA: A Webserver for Aiding Protein Drug Design by Artificial Intelligence and Classical Algorithm", Computational and Structural Biotechnology Journal, Volume 19, pp. 3573-3579, June 2021.

[270] Yifan Zhang, Peilin Zhao, Shuaicheng Niu, Qingyao Wu, Jiezhang Cao, Junzhou Huang and Mingkui Tan, "Online Adaptive Asymmetric Active Learning with Limited Budgets", IEEE Transactions on Knowledge and Data Engineering, Volume 33, Issue 6, June 2021.

[269] Yueping Liu, Xinran Wang, Liang Wang, Hong Bu, Ningning Zhang, Meng Yue, Zhanli Jia, Lijing Cai, Jiankun He, Yanan Wang, Xin Xu, Shengshui Li, Kaiwen Xiao, Kezhou Yan, Kuan Tian, Xiao Han, Junzhou Huang and Jianhua Yao, "How Can Artificial Intelligence Models Assist PD-L1 Expression Scoring in Breast Cancer: Results of Multi-institutional Ring Studies", NPJ Breast Cancer 7, 61, Volume 7, Issue 1, May 2021.

[268] Yuzhi Guo, Jiaxiang Wu, Hehuan Ma, Sheng Wang and Junzhou Huang, "EPTool: A New Enhancing PSSM Tool for Protein Secondary Structure Prediction", Journal of Computational Biology, Volume 28, Number 4, April 2021.

[267] Yuzhi Guo, Jiaxiang Wu, Hehuan Ma, Sheng Wang and Junzhou Huang, "Comprehensive Study of Bagging MSA Learning for Protein Structure Property Prediction", Journal of Computational Biology,Volume 28, Number 4, April 2021. [CODE]

[266] Lijing Cai, Kezhou Yan, Hong Bu, Meng Yue, Pei Dong, Xinran Wang, Lina Li, Kuan Tian, Haocheng Shen, Jun Zhang, Jiuyan Shang, Shuyao Niu, Dandan Han, Chen Ren, Junzhou Huang, Xiao Han, Jianhua Yao, Yueping Liu, ``Improving Ki-67 Assessment Concordance with AI-Empowered Microscope: A Multi-institutional Ring Study", Histopathology, April 2021.

[265] Zeheng Li, Shiwei Zhou, Junzhou Huang, Lifeng Yu and Mingwu Jin, "Investigation of Low-Dose CT Image Denoising Using Unpaired Deep Learning Methods", IEEE Transactions on Radiation and Plasma Medical Sciences, Volume 5, Issue 2, March 2021.

[264] Hehuan Ma, Weizhi An, Yuhong Wang, Hongmao Sun, Ruili Huang and Junzhou Huang, "Deep Graph Learning with Property Augmentation for Predicting Drug-Induced Liver Injury", Chemical Research in Toxicology, Volume 34, Issue 2, pp. 495-506, February 2021.

[263] Peng Sun, Jiaxiang Wu, Songyuan Li, Peiwen Lin, Junzhou Huang and Xi Li, "Real-Time Semantic Segmentation via Auto Depth, Downsampling Joint Decision and Feature Aggregation", International Journal of Computer Vision, Volume 129, pp.1506-1525, February 2021. (IF: 11.5)

[262] Hehuan Ma, Yu Rong, Boyang Liu, Yuzhi Guo, Chaochao Yan, and Junzhou Huang, "Gradient-Norm Based Attentive Loss for Molecular Property Prediction”, In Proc. of IEEE International Conference on Bioinformatics and Biomedicine, BIBM’21, December 2021.

[261] Xiaohan Xing, Fan Yang, Hang Li, Jun Zhang, Yu Zhao, Mingxuan Gao, Junzhou Huang, and Jianhua Yao, "An Interpretable Multi-Level Enhanced Graph Attention Network for Disease Diagnosis with Gene Expression Data”, In Proc. of IEEE International Conference on Bioinformatics and Biomedicine, BIBM’21, December 2021.

[260] Heng Chang, Yu Rong, Tingyang Xu, Yatao Bian, Shiji Zhou, Xin Wang, Junzhou Huang, Wenwu Zhu, "Not All Low-Pass Filters are Robust in Graph Convolutional Networks", In Proc. of the 35th Annual Conference on Neural Information Processing Systems, NeurIPS'21, December 2021.

[259] Huaxiu Yao, Ying Wei, Long-Kai Huang, Ding Xue, Junzhou Huang, Zhenhui Li, "Functionally Regionalized Knowledge Transfer for Low-resource Drug Discovery", In Proc. of the 35th Annual Conference on Neural Information Processing Systems, NeurIPS'21, December 2021.

[258] Yuzhao Chen, Yatao Bian, Jiying Zhang, Xi Xiao, Tingyang Xu, Yu Rong and Junzhou Huang, "Towards Diversified and Self-Corrected Graph Representation Learning", In Proc. of the IEEE International Conference on Big Knowledge, ICBK'21, Auckland, New Zealand, December 2021.

[257] Zhehan Liang, Chenxin Li, Yunlong Zhang, Yu Rong, Yue Huang, Tingyang Xu, Xinghao Ding and Junzhou Huang, “Unsupervised Large-Scale Social Network Alignment via Cross Network Embedding”, In Proc. of the 30th ACM International Conference on Information and Knowledge Management, CIKM’21, November 2021.

[256] Heng Chang, Yu Rong, Wenbing Huang, Tingyang Xu, Somayeh Sojoudi, Junzhou Huang and Wenwu Zhu, "Spectral Graph Attention Network with Fast Eigen-approximation", In Proc. of the 30th ACM International Conference on Information and Knowledge Management, CIKM’21, November 2021.

[255] Kangfei Zhao, Yu Rong, Jeffrey Xu Yu, Wenbing Huang, Junzhou Huang and Hao Zhang, "Graph Ordering: Towards the Optimal by Learning", In Proc. of International Conference on Web Information Systems Engineering, WISE’21, Melbourne, Australia, October 2021.

[254] Jinyu Yang, Chunyuan Li, Weizhi, Hehuan Ma, Yuzhi Guo, Yu Rong, Peilin Zhao, Junzhou Huang, "Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation", In Proc. of International Conference on Computer Vision, ICCV'21, October 2021.

[253] Hang Li, Fan Yang, Yu Zhao, Xiaohan Xing, Jun Zhang, Mingxuan Gao, Junzhou Huang, Liansheng Wang and Jianhua Yao, "DT-MIL: Deformable Transformer for Multi-instance Learning on Histopathological Image", In Proc. of the 24th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'21, Strasbourg, France, September 2021.

[252] Jiangpeng Yan, Hanbo Chen, Kang Wang, Yan Ji, Yuyao Zhu, Jingjing Li, Dong Xie, Zhe Xu, Junzhou Huang, Shuqun Cheng, Xiu Li and Jianhua Yao, "Hierarchical Attention Guided Framework for Multi-resolution Collaborative Whole Slide Image Segmentation", In Proc. of the 24th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'21, Strasbourg, France, September 2021.

[251] Xiyue Wang, Sen Yang, Jun Zhang, Minghui Wang, Jing Zhang, Wei Yang, Junzhou Huang and Xiao Han, "TransPath: Transformer-based Self-supervised Learning for Histopathological Image Classification", In Proc. of the 24th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'21, Strasbourg, France, September 2021.

[250] Hanbo Chen, Kang Wang, Yuyao Zhu, Jiangpeng Yan, Yan Ji, Jingjing Li, Dong Xie, Junzhou Huang, Shuqun Cheng and Jianhua Yao, "From Pixel to Whole Slide: Automatic Detection of Microvascular Invasion in Hepatocellular Carcinoma on Histopathological Image via Cascaded Networks", In Proc. of the 24th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'21, Strasbourg, France, September 2021.

[249] Hang Li, Fan Yang, Xiaohan Xing, Yu Zhao, Jun Zhang, Yueping Liu, Mengxue Han, Junzhou Huang, Liansheng Wang and Jianhua Yao, "Multi-modal Multi-instance Learning using Weakly Correlated Histopathological Images and Tabular Clinical Information", In Proc. of the 24th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'21, Strasbourg, France, September 2021.

[248] Heng Chang, Yu Rong, Tingyang Xu, Wenbing Huang, Somayeh Sojoudi, Junzhou Huang and Wenwu Zhu, "Spectral Graph Attention Network with Fast Eigen-approximation", The KDD Workshop on Deep Learning on Graphs: Method and Applications, DGL'21, Singapore, August 2021.

[247] Ying Wei, Peilin Zhao and Junzhou Huang, "Meta-learning Hyperparameter Performance Prediction with Neural Processes", In Proc. of the 38th International Conference on Machine Learning, ICML’21, July 2021.

[246] Xuefeng Du, Jingfeng Zhang, Bo Han, Tongliang Liu, Yu Rong, Gang Niu, Junzhou Huang and Masashi Sugiyama, "Learning Diverse-Structured Networks for Adversarial Robustness", In Proc. of the 38th International Conference on Machine Learning, ICML’21, July 2021.

[245] Huaxiu Yao, Long-Kai Huang, Linjun Zhang, Ying Wei, Li Tian, James Zou, Junzhou Huang and Zhenhui Li, "Improving Generalization in Meta-learning via Task Augmentation", In Proc. of the 38th International Conference on Machine Learning, ICML’21, July 2021.

[244] Yuzhao Chen, Yatao Bian, Xi Xiao, Yu Rong, Tingyang Xu and Junzhou Huang, "On Self-Distilling Graph Neural Network", In Proc. of the 30th International Joint Conference on Artificial Intelligence, IJCAI’21, Montreal, Canada, August 2021.

[243] Junchi Yu, Tingyang Xu, Yu Rong, Yatao Bian, Junzhou Huang and Ran He, "Graph Information Bottleneck for Subgraph Recognition", In Proc. of International Conference on Learning Representations, ICLR’21, Vienna, Austria, May 2021.

[242] Chaoyang He, Keshav Balasubramanian, Emir Ceyani, Yu Rong, Peilin Zhao, Junzhou Huang, Murali Annavaram and Salman Avestimehr, "FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks", The ICLR Workshop on Distributed and Private Machine Learning, DPML'21, Vienna, Austria, May 2021.

[241] Kangfei Zhao, Jeffrey Xu Yu, Yu Rong, Ming Liao and Junzhou Huang, "Towards Expectation-Maximization by SQL in RDBMS", In Proc. of International Conference on Database Systems for Advanced Applications, DASFAA’21, Taibei, Taiwan, April 2021.

[240] Zihan Wu, Rongbo Shen, Junzhou Huang, Liangsheng Wang and Jianhua Yao, "Strongly Supervised Mitosis Detection in Breast Histopathology Images Using Weak Labels", In Proc. of the IEEE International Symposium on Biomedical Imaging, ISBI’21, April 2021.

[239] Jinyu Yang, Peilin Zhao, Yu Rong, Chaochao Yan, Chunyuan Li, Hehuan Ma and Junzhou Huang, “Hierarchical Graph Capsule Network”, In Proc. of the Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI’21, Vancouver, Canada, February 2021. [CODE]

[238] Qin Wang, Boyuan Wang, Zhenlei Xu, Jiaxiang Wu, Peilin Zhao, Zhen Li, Sheng Wang, Junzhou Huang and Shuguang Cui, “PSSM-Distil: Protein Secondary Structure Prediction (PSSP) on Low-Quality PSSM by Knowledge Distillation with Contrastive Learning”, In Proc. of the Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI’21, Vancouver, Canada, February 2021.

[237] Zhen Chen, Jun Zhang, Shuanlong Che, Junzhou Huang, Xiao Han, Yixuan Yuan, “Diagnose Like A Pathologist: Weakly-Supervised Pathologist-Tree Network for Slide-Level Immunohistochemical Scoring”, In Proc. of the Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI’21, Vancouver, Canada, February 2021.

[236] Siqi Yang, Jun Zhang, Junzhou Huang, Brian Lovell and Xiao Han, “Minimizing Labeling Cost for Nuclei Instance Segmentation and Classificationwith Cross domain Images and Weak Labels”, In Proc. of the Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI’21, Vancouver, Canada, February 2021.

[235] Jinyu Yang, Weizhi An, Chaochao Yan, Peilin Zhao and Junzhou Huang, "Context-Aware Domain Adaptation in Semantic Segmentation", In Proc. of the IEEE Winter Conference on Applications of Computer Vision, WACV’21, January 2021.

[234] Junzhou Huang and Ruoyu Li, “Fast Regions-of-Interest Detection in Whole Slide Histopathology Images”, Histopathology and Liquid Biopsy, IntechOpen, November 2020.

[233] Jiawen Yao, Xinliang Zhu, Jitendra Jonnagaddala, Nicholas Hawkins and Junzhou Huang, "Whole Slide Images based Cancer Survival Prediction using Attention Guided Deep Multiple Instance Networks", Medical Image Analysis, Volume 65, October 2020. [CODE]

[232] Qingpin Xiao, Lei Wang, Shreyas Supekar, Tao Shen, Heng Liu, Fei Ye, Junzhou Huang, Hao Fan, Zhiyi Wei and Cheng Zhang, "Structure of Human Steroid 5a-reductase 2 with the Anti-androgen Drug Finasteride", Nature Communications, 11-5430, October 2020.

[231] Rui Cao, Fan Yang, Si-Cong Ma, Li Liu, Yu Zhao, Yan Li, De-Hua Wu, Tongxin Wang, Wei-Jia Lu, Wei-Jing Cai, Hong-Bo Zhu, Xue-Jun Guo, Yu-Wen Lu, Jun-Jie Kuang, Wen-Jing Huan, Wei-Min Tang, Kun Huang, Junzhou Huang, Jianhua Yao, Zhong-Yi Dong, "Development and Interpretation of a Pathomics-based Model for the Prediction of Microsatellite Instability in Colorectal Cancer", Theranostics, Volume 10(24), pp.11080-11091, October 2020.

[230] Qifeng Bai, Shuoyan Tan, Tingyang Xu, Huanxiang Liu, Junzhou Huang, Xiaojun Yao, "MolAICal: a Soft Tool for 3D Drug Design of Protein Targets by Artificial Intelligence and Classical Algorithm”, Briefings in Bioinformatics, August 2020.

[229] Wenhua Liang, Jianhua Yao, Ailan Chen, Qingquan Lv, Mark Zanin, Jun Liu, SookSan Wong, Yimin Li, Jiatao Lu, Hengrui Liang, Guoqiang Chen, Haiyan Guo, Jun Guo, Rong Zhou, Limin Ou, Niyun Zhou, Hanbo Chen, Fan Yang, Xiao Han, Wenjing Huan, Weimin Tang, Weijie Guan, Zisheng Chen, Yi Zhao, Ling Sang, Yuanda Xu, Wei Wang, Shiyue Li, Ligong Lu, Nuofu Zhang, Nanshan Zhong*, Junzhou Huang* and Jianxing He*, “Early Triage of Critically Ill COVID-19 Patients Using Deep Learning”, Nature Communications, 11-3543, July 2020.

[228] Yifan Zhang, Ying Wei, Qingyao Wu, Peilin Zhao, Shuaicheng Niu, Junzhou Huang and Mingkui Tan, "Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis", IEEE Transactions on Image Processing, Volume 29, pp. 7834-7844, July 2020.

[227] Xiaoshuang Chen, Yin Zheng, Peilin Zhao, Zhuxi Jiang, Wenye Ma and Junzhou Huang, "A Generalized Locally Linear Factorization Machine with Supervised Variational Encoding", IEEE Transactions on Knowledge and Data Engineering, Volume 32, pp. 1036-1049, June 2020.

[226] Xuefei Ning, Yin Zheng, Zhuxi Jiang, Yu Wang, Huazhong Yang, Junzhou Huang and Peilin Zhao, "Nonparametric Topic Modeling with Neural Inference", Neurocomputing, Volume 399, pp. 296-306, 2020.

[225] Yuzhi Guo, Jiaxiang Wu, Hehuan Ma, Jinyu Yang, Xinliang Zhu, and Junzhou Huang, "WeightAln: Weighted Homologous Alignment for Protein Structure Property Prediction", IEEE International Conference on Bioinformatics and Biomedicine, BIBM'20, Seout, Korea, December 2020.

[224] Yuzhi Guo, Jiaxiang Wu, Hehuan Ma, Sheng Wang, and Junzhou Huang, "Protein Ensemble Learning with Atrous Spatial Pyramid Networks for Secondary Structure Prediction", IEEE International Conference on Bioinformatics and Biomedicine, BIBM'20, Seout, Korea, December 2020.

[223] Hehuan Ma, Chaochao Yan, Yuzhi Guo, Sheng Wang, Yuhong Wang, Hongmao Sun and Junzhou Huang, "Improving Molecular Property Prediction on Limited Data with Deep Multi-Label Learning", IEEE BIBM Workshop on Machine Learning and Artificial Intelligence in Bioinformatics and Medical Informatics, MABM'20, Seout, Korea, December 2020.

[222] Hehuan Ma, Yatao Bian, Yu Rong, Wenbing Huang, Tingyang Xu, Weiyang Xie, Geyan Ye and Junzhou Huang, “Multi-View Graph Neural Networks for Molecular Property Prediction”, In Proc. of the Machine Learning for Molecules Workshop at NeurIPS 2020, Vancouver, Canada, December 2020.

[221] Chaochao Yan, Qianggang Ding, Peilin Zhao, Shuangjia Zheng, Jinyu Yang, Yang Yu and Junzhou Huang, "RetroXpert: Decompose Retrosynthesis Prediction Like A Chemist", In Proc. of the 34th Annual Conference on Neural Information Processing Systems, NIPS’20, Vancouver, Canada, December 2020.

[220] Yikai Wang, Wenbing Huang, Fuchun Sun, Tingyang Xu, Yu Rong and Junzhou Huang, "Deep Multimodal Fusion by Channel Exchanging", In Proc. of the 34th Annual Conference on Neural Information Processing Systems, NIPS’20, Vancouver, Canada, December 2020.

[219] Yu Rong, Yatao Bian, Tingyang Xu, Weiyang Xie, Ying Wei, Wenbing Huang and Junzhou Huang, "GROVER: Self-Supervised Message Passing Transformer on Large-scale Molecular Graphs", In Proc. of the 34th Annual Conference on Neural Information Processing Systems, NIPS’20, Vancouver, Canada, December 2020.

[218] Jiaxing Wang, Haoli Bai, Jiaxiang Wu, Xupeng Shi, Junzhou Huang, Irwin King, Michael Lyu and Jian Cheng , "Revisiting Parameter Sharing for Automatic Neural Channel Number Search", In Proc. of the 34th Annual Conference on Neural Information Processing Systems, NIPS’20, Vancouver, Canada, December 2020.

[217] Sifan Wu, Xi Xiao, Qianggang Ding, Peilin Zhao, Ying Wei and Junzhou Huang, “Adversarial Sparse Transformer for Time Series Forecasting”, In Proc. of the 34th Annual Conference on Neural Information Processing Systems, NIPS’20, Vancouver, Canada, December 2020.

[216] Jia Li, Jianwei Yu, Jiajin Li, Honglei Zhang, Kangfei Zhao, Yu Rong, Hong Cheng and Junzhou Huang, “Dirichlet Graph Variational Autoencoder”, In Proc. of the 34th Annual Conference on Neural Information Processing Systems, NIPS’20, Vancouver, Canada, December 2020.

[215] Ashwin Raju, Jiawen Yao, Mohammad Minhazul Haq, Jitendra Jonnagaddala and Junzhou Huang, "Graph Attention Multi-instance Learning for Accurate Colorectal Cancer Staging", In Proc. of the 22nd Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'20, Lima, Peru, October 2020.

[214] Ashwin Raju, Zhanghexuan Ji, Chi Tung Cheng, Jinzheng Cai, Junzhou Huang, Jing Xiao, Le Lu, ChienHung Liao and Adam Harrison, "User-Guided Domain Adaptation for Rapid Annotation from User Interactions: A Study on Pathological Liver Segmentation", In Proc. of the 22nd Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'20, Lima, Peru, October 2020.

[213] Zijian Zhang, Hong Shang, Han Zheng, Xiaoning Wang, Jiajun Wang, Zhongqian Sun, Junzhou Huang and Jianhua Yao, "Asynchronous in Parallel Detection and Tracking (AIPDT): Real-time Robust Polyp Detection", In Proc. of the 22nd Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'20, Lima, Peru, October 2020.

[212] Chaochao Yan, Sheng Wang, Jinyu Yang, Tingyang Xu and Junzhou Huang, "Re-balancing Variational Autoencoder Loss for Molecule Sequence Generation", In Proc. of the 11th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, ACM BCB'20, September 2020.

[211] Jinyu Yang, Weizhi An, Sheng Wang, Xinliang Zhu, Chaochao Yan and Junzhou Huang, "Label-Driven Reconstruction for Domain Adaptation in Semantic Segmentation", In Proc. of The 16th European Conference on Computer Vision, ECCV'20, Glasgow, United Kingdom, August 2020.

[210] Ashwin Raju, Chi-Tung Cheng, Yuankai Huo, Jinzheng Cai, Junzhou Huang, Jing Xiao, Le Lu, ChienHung Liao and Adam P Harrison, "Co-Heterogeneous and Adaptive Segmentation from Multi-Source and Multi-Phase CT Imaging Data: A Study on Pathological Liver and Lesion Segmentation", In Proc. of The 16th European Conference on Computer Vision, ECCV'20, Glasgow, United Kingdom, August 2020.

[209] Kuo Zhong, Ying Wei, Chun Yuan, Haoli Bai and Junzhou Huang, "TranSlider: Transfer Ensemble Learning from Exploitation to Exploration", In Proc. of The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD'20, San Diego, CA, USA, August 2020.

[208] Yong Guo, Yaofo Chen, Yin Zheng, Peilin Zhao, Jian Chen, Junzhou Huang and Mingkui Tan, "Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search", In Proc. of International Conference on Machine Learning, ICML'20, Vienna, Austria, July 2020.

[207] Mohammad Minhazul Haq and Junzhou Huang, "Adversarial Domain Adaptation for Cell Segmentation", In Proc. of The Conference on Medical Imaging with Deep Learning, Montreal, Canada, July 2020.

[206] Yuzhi Guo, Jiaxiang Wu, Hehuan Ma, Sheng Wang and Junzhou Huang, "Bagging MSA Learning: Enhancing Low-quality PSSM with Deep Learning for Accurate Protein Structure Property Prediction", In Proc. of The 24th International Conference on Research in Computational Molecular Biology, RECOMB'20, Padova, Italy, May 2020. [CODE]

[205] Han Zheng, Hong Shang, Zhongqian Sun, Xinghui Fu, Jianhua Yao, Junzhou Huang, "Supervised Augmentation: Leverage Strong Annotation for Limited Data", In Proc. of The Sixteenth IEEE International Symposium on Biomedical Imaging, ISBI'20, Coralville, IA, April 2020.

[204] Zhen Peng, Wenbing Huang, Minnan Luo, Qinghua Zheng, Yu Rong, Tingyang Xu and Junzhou Huang, "Graph Representation Learning via Graphical Mutual Information Maximization", In Proc. of International World Wide Web Conference, WWW'20, Taibei, Tanwan, China, April 2020.

[203] Jia Li, Honglei Zhang, Zhichao Han, Yu Rong, Hong Cheng and Junzhou Huang, "Adversarial Attack on Community Detection by Hiding Individuals", In Proc. of International World Wide Web Conference, WWW'20, Taibei, Tanwan, China, April 2020.

[202] Yu Rong, Wenbing Huang, Tingyang Xu, Junzhou Huang, "DropEdge: Towards Deep Graph Convolutional Networks on Node Classification", In Proc. of International Conference on Learning Representations, ICLR'20, Addis Ababa, Ethiopia, April 2020.

[201] Dongze Lian, Yin Zheng, Yintao Xu, Yanxiong Lu, Leyu Lin, Peilin Zhao, Junzhou Huang, Shenghua Gao, "Towards Fast Adaptation of Neural Architectures with Meta Learning", In Proc. of International Conference on Learning Representations, ICLR'20, Addis Ababa, Ethiopia, April 2020.

[200] Zeping Yu, Rui Cao,Qiyi Tang, Sen Nie, Junzhou Huang and Shi Wu, "Order Matters: Semantic-Aware Neural Networks for Binary Code Similarity Detection", In Proc. of the Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI'20, NYC, New York, USA, February 2020.

[199] Xiaoming Shi, Haifeng Hu, Wanxiang Che, Zhongqian Sun, Ting Liu and Junzhou Huang, "Understanding Medical Conversations with Scattered Keyword Attention and Weak Supervision from Responses", In Proc. of the Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI'20, NYC, New York, USA, February 2020.

[198] Tian Bian, Xi Xiao, Tingyang Xu, Peilin Zhao, Wenbing Huang, Yu Rong and Junzhou Huang, "Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks", In Proc. of the Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI'20, NYC, New York, USA, February 2020.

[197] Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh Chawla, Zhenhui Li, "Graph Few-shot Learning via Knowledge Transfer", In Proc. of the Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI'20, NYC, New York, USA, February 2020.

[196] Heng Chang, Yu Rong, Tingyang Xu, Wenbing Huang, Honglei Zhang, Peng Cui, Wenwu Zhu and Junzhou Huang, "A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models", In Proc. of the Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI'20, NYC, New York, USA, February 2020.

2019

[195] Xiaoming Huang, Yin Zheng, Junzhou Huang, Yu-Jin Zhang, "50 FPS Object-Level Saliency Detection via Maximally Stable Region", IEEE Transactions on Image Processing, Volume 29, pp. 1384-1396, September 2019.

[194] Chao Li, Xinggang Wang, Wenyu Liu, Longin Jan Lateckib, Bo Wang and Junzhou Huang, "Weakly Supervised Mitosis Detection in Breast Histopathology Images Using Concentric Loss", Medical Image Analysis, Volume 53, pp.165-178, April 2019.

[193] Peilin Zhao, Yifan Zhang, Min Wu, Steven C. H. Hoi, Mingkui Tan and Junzhou Huang, "Adaptive Cost-sensitive Online Classification", IEEE Transactions on Knowledge and Data Engineering, Volume 31, No. 2, pp.214-228, February 2019.

[192] Chao Yang, Xiaojian Ma, Wenbing Huang, Fuchun Sun, Huaping Liu, Junzhou Huang and Chuang Gan, "Imitation Learning from Observations by Minimizing Inverse Dynamics Disagreement", In Proc. of the 33rd Annual Conference on Neural Information Processing Systems, NIPS'19, Vancouver, Canada, December 2019.

[191] Yong Guo, Yin Zheng, Mingkui Tan, Qi Chen, Jian Chen, Peilin Zhao and Junzhou Huang, "NAT: Neural Architecture Transformer for Accurate and Compact Architectures", In Proc. of the 33rd Annual Conference on Neural Information Processing Systems, NIPS'19, Vancouver, Canada, December 2019.

[190] Ho Chung Leon Law, Peilin Zhao, Lucian Chan, Junzhou Huang and Dino Sejdinovic, "Hyperparameter Learning via Distributional Transfer", In Proc. of the 33rd Annual Conference on Neural Information Processing Systems, NIPS'19, Vancouver, Canada, December 2019.

[189] Xingyu Cai, Tingyang Xu, Jinfeng Yi, Junzhou Huang and Sanguthevar Rajasekaran, "DTWNet: a Dynamic Time Warping Network", In Proc. of the 33rd Annual Conference on Neural Information Processing Systems, NIPS'19, Vancouver, Canada, December 2019.

[188] Jie Liu, Yu Rong, Martin Takác and Junzhou Huang, "Accelerating Distributed Stochastic L-BFGS by sampled 2nd-Order Information", The NeurIPS Workshop on Beyond First Order Methods in Machine Learning Systems, Vancouver, Canada, December 2019.

[187] Ying Wei, Peilin Zhao, Huaxiu Yao, Junzhou Huang, "Transferable Neural Processes for Hyperparameter Optimization", The NeurIPS Workshop on Meta Learning, Vancouver, Canada, December 2019.

[186] Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh Chawla, Zhenhui Li, "Graph Few-shot Learning via Knowledge Transfer", The NeurIPS Workshop on Graph Representation Learning, Vancouver, Canada, December 2019.

[185] Yifan Zhang, Ying Wei, Peilin Zhao, Shuaicheng Niu, Qingyao Wu, Mingkui Tan, Junzhou Huang, "Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis", The NeurIPS Workshop on Medical Imaging Meets NeurIPS, Vancouver, Canada, December 2019.

[184] Zeheng Li, Junzhou Huang, Lifeng Yu, Yujie Chi, Mingwu Jin, "Low-Dose CT Image Denoising Using Cycle-Consistent Adversarial Networks”, In Proc. of IEEE Nuclear Science Symposium and Medical Imaging Conference, NSSMIC’19, Manchester, UK, October 2019.

[183] Guangyao Shen, Wenbing Huang, Chuang Gan, Mingkui Tan, Junzhou Huang, Wenwu Zhu, Boqing Gong, "Facial Image-to-Video Translation by a Hidden Affine Transformation", In Proc. of the 27th ACM International Conference on Multimedia, Nice, France, October 2019.

[182] Runhao Zeng, Wenbing Huang, Chuang Gan, Mingkui Tan, Yu Rong, Peilin Zhao and Junzhou Huang, "Graph Convolutional Networks for Temporal Action Localization", In Proc. of the 17th International Conference on Computer Vision, ICCV'19, Seoul, Korea, October 2019.

[181] Jiawen Yao, Jinzheng Cai, Dong Yang, Daguang Xu and Junzhou Huang, "Integrating 3D Geometry of Organ for Improving Medical Imaging Segmentation", In Proc. of the 21st Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'19, Shenzhen, China, October 2019.

[180] Jiawen Yao, Xinliang Zhu and Junzhou Huang, "Deep Multi-Instance Learning for Survival prediction from Whole Slide Images", In Proc. of the 21st Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'19, Shenzhen, China, October 2019. [CODE]

[179] Yifan Zhang, Hanbo Chen, Ying Wei, Peilin Zhao, Jiezhang Cao, Mingkui Tan, Qingyao Wu, Xinjuan Fan, Xiaoying Lou, Hailing Liu, Jinlong Hou, Xiao Han, Jianhua Yao and Junzhou Huang, "From Whole Slide Imaging to Microscopy: Deep Microscopy Adaptation Network for Histopathology Cancer Image Classification", In Proc. of the 21st Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'19, Shenzhen, China, October 2019.

[178] Hanbo Chen, Xiao Han, Xinjuan Fan, Xiaoying Lou, Hailing Liu, Junzhou Huang and Jianhua Yao, "Rectified Cross-Entropy and Upper Transition Loss for Weakly Supervised Whole Slide Image Classifier", In Proc. of the 21st Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'19, Shenzhen, China, October 2019.

[177] Hong Shang, Zhongqian Sun, Wei Yang, Xinghui Fu, Han Zheng, Jia Chang and Junzhou Huang, "Leveraging Other Datasets for Medical Imaging Classification: Evaluation of Transfer, Multi-task and Semi-supervised Learning", In Proc. of the 21st Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'19, Shenzhen, China, October 2019.

[176] Sheng Wang, Yuzhi Guo, Yuhong Wang, Hongmao Sun and Junzhou Huang, "SMILES-BERT: Large Scale Unsupervised Pre-Training for Molecular Property Prediction", In Proc. of The 10th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, BCB'19, Niagara Falls, NY, USA, September 2019. [CODE]

[175] Hanyu Peng, Jiaxiang Wu, Shifeng Chen and Junzhou Huang, “Collaborative Channel Pruning for Deep Networks", In Proc. of International Conference on Machine Learning, ICML'19, Long Beach, CA, USA, June 2019.

[174] Xiaoshuang Chen, Yin Zheng, Jiaxing Wang, Wenye Ma and Junzhou Huang, “RaFM: Rank-Aware Factorization Machines", In Proc. of International Conference on Machine Learning, ICML'19, Long Beach, CA, USA, June 2019.

[173] Huaxiu Yao, Ying Wei, Junzhou Huang and Zhenhui Li, “Hierarchically Structured Meta-learning", In Proc. of International Conference on Machine Learning, ICML'19, Long Beach, CA, USA, June 2019.

[172] Sheng Wang, Zheng Xu, Chaochao Yan and Junzhou Huang, “Graph Convolutional Nets for Tool Presence Detection in Surgical Videos", In Proc. of The 26th International Conference on Information Processing in Medical Imaging, IPMI'19, Hong Kong, China, June 2019. [CODE]

[171] Chaoqi Chen, Weiping Xie, Tingyang Xu, Wenbing Huang, Yu Rong, Xinghao Ding, Yue Huang and Junzhou Huang, “Progressive Feature Alignment for Unsupervised Domain Adaptation", In Proc. of IEEE Conference on Computer Vision and Pattern Recognition, CVPR'19, Long Beach, CA, USA, June 2019.

[170] Jia Li, Yu Rong, Hong Cheng, Helen Meng, Wenbing Huang and Junzhou Huang, "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective", In Proc. of International World Wide Web Conference, WWW'19, San Francisco, CA, USA, May 2019.

[169] He Zheng, Hanbo Chen, Junzhou Huang, Xuzhi Li, Xiao Han and Jianhua Yao, "Polyp Tracking in Video Colonoscopy Using Optical Flow With an On-The-Fly Trained CNN", In Proc. of The Sixteenth IEEE International Symposium on Biomedical Imaging, ISBI'19, Venice, Italy, April 2019.

[168] Bo Liu, Xiaotong Yuan, Lezi Wang, Qingshan Liu, Junzhou Huang, Dimitris Metaxas, "Distributed Inexact Newton-type Pursuit for Non-convex Sparse Learning", In Proc. of The 22nd International Conference on Artificial Intelligence and Statistics, AISTATS'19, Naha, Okinawa, Japan, April 2019.

[167] Yue Yu, Jiaxiang Wu and Junzhou Huang, "Exploring Fast and Communication Efficient Algorithms in Large-scale Distributed Networks", In Proc. of The 22nd International Conference on Artificial Intelligence and Statistics, AISTATS'19, Naha, Okinawa, Japan, April 2019.

[166] Zebang Shen, Hui Qian, Cong Fang, Peilin Zhao and Junzhou Huang, "Complexities in Projection-Free Stochastic Non-convex Minimization", In Proc. of The 22nd International Conference on Artificial Intelligence and Statistics, AISTATS'19, Naha, Okinawa, Japan, April 2019.

[165] Lijie Fan, Wenbing Huang, Chuang Gan, Junzhou Huang and Boqing Gong, "Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation", In Proc. of The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI'19, Honolulu, Hawaii, USA, February 2019. (Oral Presentation)

[164] Lichen Wang, Jiaxiang Wu, Shaolun Huang, Lizhong Zheng, Xiangxiang Xu, Lin Zhang and Junzhou Huang, "An Efficient Approach to Informative Feature Extraction from Multimodal Data", In Proc. of The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI'19, Honolulu, Hawaii, USA, February 2019.

[163] Zheng Xu, Sheng Wang, Yeqing Li, Feiyun Zhu and Junzhou Huang, "PRIM: An Efficient Preconditioning Iterative Reweighted Least Squares Method for Parallel Brain MRI Reconstruction", Neuroinformatics, Volume 16, Issue 3-4, pp. 425-430, October 2018. [CODE]

[162] Chen Chen, Lei He, Hongsheng Li and Junzhou Huang, "Fast Iteratively Reweighted Least Squares Algorithms for Analysis-Based Sparse Reconstruction", Medical Image Analysis, Volume 49, pp.141-152, October 2018. [CODE]

[161] Yeqing Li, Chen Chen, Fei Yang and Junzhou Huang, "Hierarchical Sparse Representation for Robust Image Registration", IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 40, Issue 9, pp.2151-2164, September 2018. [CODE]

[160] Xiaoming Huang, Yin Zheng, Junzhou Huang and Yujin Zhang, "A Minimum Barrier Distance Based Saliency Box for Object Proposals Generation", IEEE Signal Processing Letters, Volume 25, Issue 8, pp. 1126-1130, August 2018.

[159] Yeqing Li, Wei Liu and Junzhou Huang, "Sub-Selective Quantization for Learning Binary Code in Large-Scale Image Search", IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 40, Issue 6, pp. 1526-1532, June 2018. [CODE]

[158] Zhibin Zhu, JiawenYao, Zheng Xu, Junzhou Huang and Benxin Zhang, "A Simple Primal-dual Algorithm for Nuclear Norm and Total Variation Regularization", Neurocomputing, Volume 289, pp. 1-12, May 2018.

[157] Jiawen Yao, Zheng Xu, Xiaolei Huang and Junzhou Huang, "An Efficient Algorithm for Dynamic MRI Using Low-rank and Total Variation Regularization", Medical Image Analysis, Volume 44, pp. 14-27, February 2018. [CODE]

[156] Wenbing Huang, Tong Zhang, Yu Rong and Junzhou Huang, "Adaptive Sampling Towards Fast Graph Representation Learning", In Proc. of the 32nd Annual Conference on Neural Information Processing Systems, NIPS'18, Montreal, Canada, December 2018.

[155] Zhuangwei Zhuang, Mingkui Tan, Bohan Zhuang, Jing Liu, Jiezhang Cao, Qingyao Wu, Junzhou Huang, Jinhui Zhu, "Discrimination-aware Channel Pruning for Deep Neural Networks", In Proc. of the 32nd Annual Conference on Neural Information Processing Systems, NIPS'18, Montreal, Canada, December 2018.

[154] Xuguang Duan, Wenbing Huang, Chuang Gan, Jingdong Wang, Wenwu Zhu and Junzhou Huang, "Weakly Supervised Dense Event Captioning in Videos", In Proc. of the 32nd Annual Conference on Neural Information Processing Systems, NIPS'18, Montreal, Canada, December 2018.

[153] Ho Chung Leon Law, Peilin Zhao, Junzhou Huang and Dino Sejdinovic, "Hyperparameter Learning via Distributional Transfer", In The NIPS 2018 Workshop on Meta-Learning, Montreal, Canada, December 2018.

[152] Jiaxiang Wu, Yao Zhang, Haoli Bai, Huasong Zhong, Jinlong Hou, Wei Liu, Wenbing Huang and Junzhou Huang, "PocketFlow: An Automated Framework for Compressing and Accelerating Deep Neural Networks", In The NIPS 2018 Workshop on Compact Deep Neural Networks with Industrial Applications, Montreal, Canada, December 2018.

[151] Yongluan Yan, Xinggang Wang, Xiaojie Guo, Jiemin Fang, Wenyu Liu and Junzhou Huang, "Deep Multi-instance Learning with Dynamic Pooling", In Proc. of the 10th Asian Conference on Machine Learning, ACML'18, Beijing, China, November 2018.

[150] Peng Tang, Xinggang Wang, Angtian Wang, Yongluan Yan, Wenyu Liu, Junzhou Huang and Alan Yuille, "Weakly Supervised Region Proposed Network and Object Detection", In Proc. of The 15th European Conference on Computer Vision, ECCV'18, Munich, Germany, September 2018.

[149] Chaochao Yan, Jiawen Yao, Ruoyu Li, Zheng Xu and Junzhou Huang, "Weakly-supervised Deep Learning for Thoracic Disease Classication and Localization on Chest X-rays", In Proc. of The 9th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, BCB'18, Washington DC, USA, September 2018.

[148] Xiaoyu Zhang, Sheng Wang, Feiyun Zhu, Zheng Xu, Yuhong Wang and Junzhou Huang, "Seq3seq Fingerprint: Towards End-to-end Semi-supervised Deep Drug Discovery", In Proc. of The 9th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, BCB'18, Washington DC, USA, September 2018.

[147] Feiyun Zhu, Peng Liao, Xinliang Zhu, Jiawen Yao and Junzhou Huang, "Cohesion-driven Online Actor-Critic Reinforcement Learning for mHealth Intervention", In Proc. of The 9th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, BCB'18, Washington DC, USA, September 2018

[146] Feiyun Zhu, Jun Guo, Ruoyu Li and Junzhou Huang, "Robust Actor-Critic Contextual Bandit for Mobile Health (mHealth) Interventions", In Proc. of The 9th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, BCB'18, Washington DC, USA, September 2018.

[145] Ruoyu Li, Jiawen Yao, Xinliang Zhu, Yeqing Li and Junzhou Huang, "Graph CNN for Survival Analysis on Whole Slide Pathological Images", In Proc. of the 20th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'18, Granada, Spain, September 2018. [CODE]

[144] Feiyun Zhu, Jun Guo, Zheng Xu, Peng Liao and Junzhou Huang, "Group-driven Reinforcement Learning for Personalized mHealth Intervention", In Proc. of the 20th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'18, Granada, Spain, September 2018.

[143] Feiyun Zhu, Xinliang Zhu, Sheng Wang, Jiawen Yao, Zhichun Xiao and Junzhou Huang, "Robust Contextual Bandit via the Capped-L2 Norm for Mobile Health Intervention", In The 9th International Workshop on Machine Learning in Medical Imaging, MLMI'18, Granada, Spain, September 2018.

[142] JiaxiangWu, Weidong Huang, Junzhou Huang and Tong Zhang, "Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization", In Proc. of International Conference on Machine Learning, ICML'18, Stockholm, Sweden, July 2018.

[141] Ying Wei, Yu Zhang, Junzhou Huang, Qiang Yang, "Transfer Learning via Learning to Transfer", In Proc. of International Conference on Machine Learning, ICML'18, Stockholm, Sweden, July 2018.

[140] Jiezhang Cao, Yong Guo, Qingyao Wu, Chunhua Shen, Junzhou Huang, Mingkui Tan, "Adversarial Learning with Local Coordinate Coding", In Proc. of International Conference on Machine Learning, ICML'18, Stockholm, Sweden, July 2018.

[139] Yifan Zhang, Peilin Zhao, Jiezhang Cao, Wenye Ma, Junzhou Huang, Qingyao Wu and Mingkui Tan, "Online Adaptive Asymmetric Active Learning for Budgeted Imbalanced Data", In Proc. of ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD'18, London, UK, August 2018.

[138] Lijie Fan, Wenbing Huang, Chuang Gan, Stefano Ermon, Boqing Gong and Junzhou Huang, "End-to-End Learning of Motion Representation for Video Understanding", In Proc. of IEEE Conference on Computer Vision and Pattern Recognition, CVPR'18, Salt Lake, Utah, USA, June 2018. (Spotlight)

[137] Siyuan Zhang, Yu Rong, Yu Zheng, Hong Cheng and Junzhou Huang, "Exploiting Ranking Consistency Principle in Representation Learning for Location Promotion", In Proc. of The 23rd International Conference on Database Systems for Advanced Applications, DASFAA'18, Gold Coast, Australia, May 2018.

[136] Xiao Lin, Wenpeng Zhang, Min Zhang, Peilin Zhao, Wenwu Zhu, Jian Pei and Junzhou Huang, "Online Compact Convexified Factorization Machine", International World Wide Web Conference, WWW'18, Lyon, France, April 2018.

[135] Ruoyu Li, Sheng Wang, Feiyun Zhu and Junzhou Huang, "Adaptive Graph Convolutional Neural Networks", In Proc. of The Thirty-Second AAAI Conference on Artificial Intelligence, AAAI'18, New Orleans, USA, February 2018. (Oral Presentation) [CODE]

2017

[134] Yuhong Wang, Junzhou Huang, Wei Li, Sheng Wang and Chuanfan Ding, "Specific and Intrinsic Sequence Patterns Extracted by Deep Learning from Intra-Protein Binding and Non-binding Peptide Fragments", Scientific Reports, November 2017.

[133] Faliu Yi, Junzhou Huang, Lin Yang, Yang Xie and Guanghua Xiao, "Automatic Extraction of Cell Nuclei from H&E-stained Histopathological Images", Journal of Medical Imaging, Volume 4, pp. 4-12, June 2017.

[132] Xin Luo, Xiao Zang, Lin Yang, Junzhou Huang, Faming Liang, Jaime Rodriguez Canales, Ignacio I. Wistuba, Adi Gazdar, Yang Xie, Guanghua Xiao, "Comprehensive Computational Pathological Image Analysis Predicts Lung Cancer Prognosis", Journal of Thoracic Oncology, Volume 12, pp.501-509, March 2017.

[131] Ruogu Fang, Ajay Gupta, Junzhou Huang, Pina Sanelli, "TENDER: TEnsor Non-local Deconvolution Enabled Radiation Reduction in CT Perfusion", NeuroComputing, Volume 229, pp. 13-22, March 2017.

[130] Junzhou Huang, Zheng Xu, "Accelerated Cell Detection with Sparse Convolution Kernels", book chapter, Deep Learning and Convolutional Neural Networks for Medical Image Computing, ISBN: 9783319429984, Springer, 2017.

[129] Wenbing Huang, Mehrtash Harandi, Tong Zhang, Lijie Fan, Fuchun Sun and Junzhou Huang, "Efficient Optimization for Linear Dynamical Systems with Applications to Clustering and Sparse Coding", In Proc. of the 31st Annual Conference on Neural Information Processing Systems, NIPS'17, Long Beach, Los Angeles, California, USA, December 2017.

[128] Jiawen Yao, Xinliang Zhu, Feiyun Zhu and Junzhou Huang, "Deep Correlational Learning for Survival Prediction from Multi-modality Data", In Proc. of the 19th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'17, Quebec City, Quebec, Canada, September 2017. (Oral Presentation) [CODE]

[127] Zheng Xu, Sheng Wang, Feiyun Zhu and Junzhou Huang, "Seq2seq Fingerprint: An Unsupervised Deep Molecular Embedding for Drug Discovery", In Proc. of the 8th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics, BCB'17, Boston, MA, August 2017. [CODE]

[126] Xinliang Zhu, Jiawen Yao, Feiyun Zhu and Junzhou Huang, "WSISA: Making Survival Prediction from Whole Slide Pathology Images", In Proc. of IEEE Conference on Computer Vision and Pattern Recognition, CVPR'17, Honolulu, Hawaii, USA, July 2017. [CODE]

[125] Sheng Wang, Ashwin Raju and Junzhou Huang, "Deep Learning Based Multi-label Classification for Surgical Tool Presence Detection in Laparoscopic Videos", In Proc. of the International Symposium on Biomedical Imaging, ISBI'17, Melbourne, Australia, April 2017.

[124] Li Shen, Wei Liu, Junzhou Huang, Yugang Jiang and Shiqian Ma, "Adaptive Proximal Average Approximation for Composite Convex Minimization", In Proc. of the Thirty-First AAAI Conference on Artificial Intelligence, AAAI'17, San Francisco, California USA, February 2017.

[123] Zheng Xu and Junzhou Huang, "A General Efficient Hyperparameter-free Algorithm for Convolutional Sparse Learning", In Proc. of the Thirty-First AAAI Conference on Artificial Intelligence, AAAI'17, San Francisco, California USA, February 2017.

[122] Menglin Jiang, Shaoting Zhang, Junzhou Huang, Lin Yang, Dimitris Metaxas, "Scalable Histopathological Image Analysis via Supervised Hashing with Multiple Features", Medical Image Analysis, Volume 34, pp. 3-12, December 2016.

[121] Xiang Yu, Junzhou Huang, Shaoting Zhang, Dimitris Metaxas, "Face Landmark Fitting via Optimized Part Mixtures and Cascaded Deformable Model", IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 38, Issue 11, pp. 2212-2226, November 2016.

[120] Chen Chen, Yeqing Li, Leon Axel and Junzhou Huang, "Real Time Dynamic MRI by Exploiting Spatial and Temporal Sparsity", Magnetic Resonance Imaging, Volume 34, Issue 4, pp. 473-482, May 2016. [CODE]

[119] Junzhou Huang, Yeqing Li, "Advanced Sparsity Techniques in Magnetic Resonance Imaging", book chapter, Machine Learning and Medical Imaging, ISBN: 978-0-12-804076-8, Elsevier Press, 2016

[118] Xinliang Zhu, Jiawen Yao and Junzhou Huang, "Deep Convolutional Neural Network for Survival Analysis with Pathological Images", IEEE International Conference on Bioinformatics and Biomedicine, BIBM'16, Shenzhen, China, December 2016.

[117] Xinliang Zhu, Jiawen Yao, Guanghua Xiao, Yang Xie, Jaime Rodriguez-Canales, Edwin R. Parra, Carmen Behrens, Ignacio I. Wistuba and Junzhou Huang, "Imaging-Genetic Data Mapping for Clinical Outcome Prediction via Supervised Conditional Gaussian Graphical Model", IEEE International Conference on Bioinformatics and Biomedicine, BIBM'16, Shenzhen, China, December 2016.

[116] Zheng Xu, Yeqing Li and Junzhou Huang, "Accelerated Sparse Optimization for Missing Data Completion", In Proc. of the 23rd International Conference on Pattern Recognition, ICPR'16, Cancun, Mexico, December 2016

[115] Zheng Xu, Junzhou Huang, "Detecting 10,000 Cells in One Second", In Proc. of the 19th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'16, Athens, Greece, October 2016. [CODE]

[114] Sheng Wang, Jiawen Yao, Zheng Xu, Junzhou Huang, "Subtype Cell Detection with an Accelerated Deep Convolution Neural Network", In Proc. of the 19th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'16, Athens, Greece, October 2016.

[113] Jiawen Yao, Sheng Wang, Xinliang Zhu, Junzhou Huang, "Clinical Imaging Biomarker Discovery for Survival Prediction on Lung Cancer Imaging Genetic Data", In Proc. of the 19th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'16, Athens, Greece, October 2016. (Oral Presentation)

[112] Xi Peng, Qiong Hu, Junzhou Huang, Dimitris Metaxas, "Track Facial Points in Unconstrained Videos", The 27th British Machine Vision Conference, BMVC'16, York, UK, September 2016.

[111] Longwen Gao, Yeqing Li, Junzhou Huang, Shuigeng Zhou, "Semi-supervised Group Sparse Representation: Model, Algorithm and Applications", In Proc. of the 22st European Conference on Artificial Intelligence, ECAI'16, Hague, August 2016.

[110] Xi Peng, Junzhou Huang, Dimitris Metaxas, "Sequential Face Alignment via Person-Specific Modeling in the Wild", In Proc. of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW'16, Las Vegas, USA, June 2016

[109] Xinliang Zhu, Jianwen Yao, Xin Luo, Guanghua Xiao, Yang Xie, Adi Gazdar and Junzhou Huang, "Lung Cancer Survival Prediction from Pathological Images and Genetic Data - An Integration Study", In Proc. of The International Symposium on Biomedical Imaging, ISBI'16, Prague, Czech Republic, April 2016.

[108] Zhongxing Peng, Zheng Xu, Junzhou Huang, "RSPIRiT: Robust Self-Consistent Parallel Imaging Reconstruction Based on Generalized Lasso", In Proc. of The International Symposium on Biomedical Imaging, ISBI'16, Prague, Czech Republic, April 2016.

[107] Yeqing Li, Junzhou Huang, Wei Liu, "Scalable Sequential Spectral Clustering", In Proc. of The Thirtieth AAAI Conference on Artificial Intelligence, AAAI'16, Phoenix, Arizona, USA, February 2016. [CODE]

2015

[106] Jinghao Zhou, Zhennan Yan, Giovanni Lasio, Junzhou Huang, Baoshe Zhang, Navesh Sharma, Karl Prado, Warren D’Souza, "Automated Compromised right Lung Segmentation Method Using a Robust Atlas-based Active Volume Model with Sparse Shape Composition Prior in CT", Computerized Medical Imaging and Graphics, Volume 46, pp. 47-55, December 2015.

[105] Ruogu Fang, Haodi Jiang, Junzhou Huang, "Tissue-Specific Sparse Deconvolution for Brain CT Perfusion", Computerized Medical Imaging and Graphics, Volume 46, pp. 64-72, December 2015.

[104] Chen Chen, Yeqing Li, Wei Liu and Junzhou Huang, "SIRF: Simultaneous Satellite Image Registration and Fusion in A Unified Framework", IEEE Transactions on Imaging Processing, Vol. 24, No.11, November 2015. [CODE]

[103] Lin Zhong, Qingshan Liu, Peng Yang, Junzhou Huang and Dimitris Metaxas, "Learning Multi-scale Active Facial Patches for Expression Analysis", IEEE Transaction on Cybernetics, Volume 45, Number 8, pp.1499-1510, August 2015.

[102] Xi Peng, Junzhou Huang, Qiong Hu, Shaoting Zhang, Ahmed Elgammal and Dimitris Metaxas, "From Circle to 3-Sphere: Head Pose Estimation by Instance Parameterization", Computer Vision and Image Understanding, Volume 136, pp.92-102, July 2015.

[101] Xiang Yu, Shaoting Zhang, Zhenan Yan, Fei Yang, Junzhou Huang, Norah Dunbar, Matthew Jensen, Judee K. Burgoon and Dimitris N. Metaxas, "Is Interactional Dissynchrony a Clue to Deception? Insights from Automated Analysis of Nonverbal Visual Cues", IEEE Transactions on Cybernetics, Volume 45, Issue 3, pp. 506-520, March 2015.

[100] Jiawen Yao, Dheeraj Ganti, Xin Luo, Guanghua Xiao, Yang Xie, Shirley Yan and Junzhou Huang, "Computer-assisted Diagnosis of Lung Cancer Using Quantitative Topology Features", 6th International Workshop on Machine Learning in Medical Imaging, MLMI'15, Munich, Germany, October 2015.

[099] Zheng Xu, Junzhou Huang, "Efficient Lung Cancer Cell Detection with Deep Convolution Neural Network", 1st International Workshop on Patch-based Techniques in Medical Imaging, PMI'15, Munich, Germany, October 2015.

[098] Hao Pan, Zheng Xu, Junzhou Huang, "An Effective Approach for Robust Lung Cancer Cell Detection", 1st International Workshop on Patch-based Techniques in Medical Imaging, PMI'15, Munich, Germany, October 2015.

[097] Ruoyu Li, Junzhou Huang, "Fast Regions-of-Interest Detection in Whole Slide Histopathology Images", 1st International Workshop on Patch-based Techniques in Medical Imaging, PMI'15, Munich, Germany, October 2015.

[096] Ruogu Fang, Ming Ni, Junzhou Huang, Qianmu Li, Tao Li, "A Efficient 4D Non-Local Tensor Total-Variation for Low-Dose CT Perfusion Deconvolution", MICCAI Workshop on Medical Computer Vision: Algorithms for Big Data, MCV'15, Munich, Germany, October 2015.

[095] Zheng Xu, Yeqing Li, Leon Axel, Junzhou Huang, "Efficient Preconditioning in Joint Total Variation Regularized Parallel MRI Reconstruction", In Proc. of the 18th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'15, Munich, Germany, October 2015.

[094] Ruoyu Li, Yeqing Li, Ruogu Fang, Shaoting Zhang, Hao Pan, Junzhou Huang, "Fast Preconditioning for Accelerated Multi-Contrast MRI Reconstruction", In Proc. of the 18th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'15, Munich, Germany, October 2015. (Oral presentation 36/810 = ~4% )

[093] Menglin Jiang, Shaoting Zhang, Junzhou Huang, Lin Yang, Dimitris Metaxas, "Joint Kernel-Based Supervised Hashing for Scalable Histopathological Image Analysis", In Proc. of the 18th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'15, Munich, Germany, October 2015. (MICCAI Young Scientist Award, 4 out of 810 submissions)

[092] Jiawen Yao, Zheng Xu, Xiaolei Huang, Junzhou Huang, "Accelerated Dynamic MRI Reconstruction with Total Variation and Nuclear Norm Regularization", In Proc. of the 18th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'15, Munich, Germany, October 2015. [CODE]

[091] Cheng Deng, Zongting Lv , Wei Liu, Junzhou Huang, Dacheng Tao, Xinbo Gao, "Multi-View Matrix Decomposition: A New Scheme for Exploring Discriminative Information", In Proc. of International Joint Conference on Artificial Intelligence, IJCAI'15, Buenos Aires, Argentina, July 2015.

[090] Yeqing Li, Chen Chen, Fei Yang and Junzhou Huang, "Deep Sparse Representation for Robust Image Registration", In Proc. of IEEE Conference on Computer Vision and Pattern Recognition, CVPR'15, Boston, USA, June 2015. [CODE]

[089] Ruogu Fang, Junzhou Huang, Wen-Ming Luh, "A Spatio-Temporal Low-rank Total Variation Approach for Denoising Arterial Spin Labeling MRI Data", In Proc. of IEEE International Symposium on Biomedical Imaging, ISBI'15, Brooklyn Bridge, NY, USA, April 2015.

[088] Chen Chen, Venkaiah Chowdary Kavuri, Xinlong Wang, Ruoyu Li, Hanli Liu, Junzhou Huang, "Multi-frequency Diffuse Optical Tomography for Cancer Detection", In Proc. of IEEE International Symposium on Biomedical Imaging, ISBI'15, Brooklyn Bridge, NY, USA, April 2015.

[087] Yeqing Li, Chen Chen, Jinghao Zhou, Junzhou Huang, "Robust Image Registration in the Gradient Domain", In Proc. of IEEE International Symposium on Biomedical Imaging, ISBI'15, Brooklyn Bridge, NY, USA, April 2015. [CODE]

[086] Xi Peng, Junzhou Huang, Qiong Hu, Shaoting Zhang, Dimitris Metaxas, "Three-Dimensional Head Pose Estimation in-the-Wild", In Proc. the 11th IEEE International Conference on Automatic Face and Gesture Recognition, FG'15, Ljubljana, Slovenia, May 2015.

[085] Yeqing Li, Feiping Nie, Heng Huang and Junzhou Huang, "Large-Scale Multi-View Spectral Clustering via Bipartite Graph", In Proc. of the Twenty-Ninth AAAI Conference on Artificial Intelligence, AAAI'15, Austin, TX, USA, Januanry 2015. [CODE]

2014

[084] Chen Chen, Fenghua Tian, Hanli Liu and Junzhou Huang, "Diffuse Optical Tomography Enhanced by Clustered Sparsity for Functional Brain Imaging", IEEE Transactions on Medical Imaging, Volume 33, Issue 12, pp. 2323-2331, December 2014. [CODE]

[083] Hongsheng Li, Xiaolei Huang, Junzhou Huang, Shaoting Zhang, "Feature Matching with Affine-Function Transformation Models", IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 36, Issue 12, pp. 2407-2422, December 2014.

[082] Junzhou Huang, Chen Chen, Leon Axel, "Fast Multi-contrast MRI Reconstruction", Magnetic Resonance Imaging, Volume 32, Issue 10, pp. 1344-1352, December 2014. [CODE]

[081] Chen Chen and Junzhou Huang, ”Exploiting the wavelet structure in Compressed Sensing MRI”, Magnetic Resonance Imaging, Volume 32, Issue 10, pp. 1377-1389, December 2014. [CODE]

[080] Chen Chen and Junzhou Huang, "The Benefit of Tree Sparsity in Accelerated MRI", Medical Image Analysis, Volume 18, Issue 6, pp. 834-842, August 2014. [CODE]

[079] Chen Chen, Yeqing Li, and Junzhou Huang, "Forest Sparsity for Multi-channel Compressive Sensing", IEEE Transactions on Signal Processing, Volume 62, Issue 11, pp. 2803-2813, June 2014. [CODE]

[078] Soheil Shafiee, Farhad Kamangar, Vassilis Athitsos, Junzhou Huang and Laleh Ghandehari, "Multimodal Sparse Representation Classification with Fisher Discriminative Sample Reduction", In Proc. of IEEE International Conference on Image Processing, ICIP'14, Paris, France, October 2014.

[077] Chen Chen, Yeqing Li, Leon Axel and Junzhou Huang, "Real Time Dynamic MRI with Dynamic Total Variation", In Proc. of the 16th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'14, Boston, USA, September 2014. [CODE]

[076] Yeqing Li, Chen Chen, Xiaolei Huang and Junzhou Huang, "Instrument Tracking via Online Learning in Retinal Microsurgery", In Proc. of the 16th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'14, Boston, USA, September 2014. [CODE] (Oral Presentation) (Best Student Paper Award Runners Up)

[075] Yeqing Li, Chen Chen, Wei Liu, and Junzhou Huang, "Sub-SelectiveQuantization for Large-Scale Image Search", In Proc. of the Twenty-Eighth AAAI Conference on Artificial Intelligence, AAAI'14, Québec, Canada, July 2014. [CODE] (Oral Presentation)

[074] Chen Chen, Zhongxing Peng, and Junzhou Huang, "O(1) Algorithms for Overlapping Group Sparsity", In Proc. of International Conference on Pattern Recognition, ICPR'14, Stockholm, Sweden, August 2014. (Oral Presentation)

[073] Yeqing Li, Chen Chen, and Junzhou Huang, "Transformation-invariant Collaborative Sub-representation", In Proc. of International Conference on Pattern Recognition, ICPR'14, Stockholm, Sweden, August 2014.

[072] Xi Peng, Junzhou Huang, Qiong Hu, Shaoting Zhang and Dimitris N. Metaxas, "Head Pose Estimation by Instance Parameterization", In Proc. of International Conference on Pattern Recognition, ICPR'14, Stockholm, Sweden, August 2014.

[071] Chen Chen, Junzhou Huang, Lei He, and Hongsheng Li, "Preconditioning for Accelerated Iteratively Reweighted Least Squares in Structured Sparsity Reconstruction", In Proc. of IEEE Conference on Computer Vision and Pattern Recognition, CVPR'14, Columbus, Ohio, USA, June 2014. [CODE] (Oral Presentation)

[070] Chen Chen, Yeqing Li, Wei Liu, and Junzhou Huang, "Image Fusion with Local Spectral Consistency and Dynamic Gradient Sparsity", In Proc. of IEEE Conference on Computer Vision and Pattern Recognition, CVPR'14, Columbus, Ohio, USA, June 2014. [CODE] (Oral Presentation)

[069] Yeqing Li, Zhongxing Peng, Junzhou Huang, Zhilin Zhang and Jae Hyun Son, "Energy Disaggregation via Hierarchical Factorial HMM", The Second International Workshop on Non-Intrusive Load Monitoring, NILM'14, Austin, TX, USA, June 2014..

[068] Junzhou Huang, Chen Chen, and Xinyi Cui, "Sparsity Driven Background Modeling and Foreground Detection", book chapter, to appear in "Background Modeling and Foreground Detection for Video Surveillance", CRC Press, July 2014.

[067] Chen Chen and Junzhou Huang, "Exploiting Both Intra-quadtree and Inter-spatial Structures for Multi-contrast MRI", In Proc. of IEEE International Symposium on Biomedical Imaging, ISBI'14, Beijing, China, April 2014. [CODE]

[066] Chen Chen, Fenghua Tian, Jixing Yao, Hanli Liu and Junzhou Huang, "2D Diffuse Optical Imaging Using Clustered Sparsity", In Proc. of IEEE International Symposium on Biomedical Imaging, ISBI'14, Beijing, China, April 2014. (Oral Presentation) [CODE]

2013

[065] Shaoting Zhang, Yiqiang Zhan, Xinyi Cui, Mingchen Gao, Junzhou Huang, Dimitris Metaxas, "3D Anatomical Shape Atlas Construction using Mesh Quality Preserved Deformable Models", Computer Vision and Image Understanding, Volume 117, Issue 9, pp. 1061-1071, September 2013.

[064] Baiyang Liu, Junzhou Huang, Casimir Kulikowski, Lin Yang, "Robust Visual Tracking Using Local Sparse Appearance Model and K-Selection", IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 35, Issue 12, pp. 2968-2981, December 2013.

[063] Chen Chen, Yeqing Li and Junzhou Huang, "Calibrationless Parallel MRI with Joint Total Variation Regularization", In Proc. of the 16th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'13, Nagoya, Japan, September 2013. [CODE]

[062] Xiang Yu, Junzhou Huang, Shaoting Zhang, Wang Yan and Dimitris Metaxas, "Pose-free Facial Landmark Fitting via Optimized Part Mixtures and Cascaded Deformable Shape Model", In Proc. of the 14th International Conference on Computer Vision, ICCV'13, Sydney, Australia, December 2013.

[061] Soheil Shafiee, Farhad Kamangar, Vassilis Athitsos and Junzhou Huang, "The Role of Dictionary Learning on Sparse Representation-based Classification", In Proc. of the 6th International Conference on Pervasive Technologies Related to Assistive Environments, PETRA'13, Rhodes Island, Greece, May 2013.

[060] Soheil Shafiee, Farhad Kamangar, Vassilis Athitsos and Junzhou Huang, "Efficient Sparse Representation Using Adaptive K-means Clustering", In International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV'13, Las Vegas, USA, July 2013.

[059] Yang Yu, Shaoting Zhang, Junzhou Huang, Dimitris Metaxas and Leon Axel, "Sparse Deformable Models with Application to Cardiac Motion Analysis", In Proc. of the 23rd Biennial International Conference on Information Processing in Medical Imaging, IPMI'13, Asilomar, CA, June 2013.

[058] Lin Zhong, Shaoting Zhang, Mingchen Gao, Junzhou Huang, Zhen Qian, Dimitris Metaxas and Leon Axel, "Papillary Muscles Analysis from High Resolution CT using Spatial-Temporal Skeleton Extraction", In Proc. of the IEEE International Symposium on Biomedical Imaging, ISBI'13, San Francisco, CA, USA, April 2013.

[057] Xiang Yu, Fei Yang, Junzhou Huang and Dimitris Metaxas, "Explicit Occlusion Detection based Deformable Fitting for Facial Landmark Localization", In Proc. of the IEEE International Conference on Automatic Face and Gesture Recognition, FG'13, Shanghai, China, April 2013.

[056] Xiang Yu, Shaoting Zhang, Zhennan Yan, Fei Yang, Junzhou Huang, Norah Dunbar, Matthew Jensen, Judee K. Burgoon and Dimitris N. Metaxas, "Is Interactional Dissynchrony a Clue to Deception: Insights from Automated Analysis of Nonverbal Visual Cues", In Proc. of the 46th Hawaii International Conference on System Sciences, HICSS'13, Wailea, HI, USA, January 2013.

2012

[055] Chen Chen, Junzhou Huang, "Compressive Sensing MRI with Wavelet Tree Sparsity", In Proc. of the 26th Annual Conference on Neural Information Processing Systems, NIPS'12, Lake Tahoe, Nevada, USA, December 2012. [CODE]

[054] Junzhou Huang, Chen Chen, Leon Axel, "Fast Multi-contrast MRI Reconstruction", In Proc. of the 15th Annual International Conf. on Medical Image Com puting and Computer Assisted Intervention, MICCAI’12, Nice, France, October 2012. [CODE]

[053] Mingchen Gao, Junzhou Huang, Xiaolei Huang, Shaoting Zhang, Dimitris Metaxas, "Simplified Labeling Process for Medical Image Segmentation", In Proc. of the 15th Annual International Conf. on Medical Image Computing and Computer Assisted Intervention, MICCAI'12, Nice, France, October 2012.

[052] Chen Chen, Junzhou Huang, "The Benefit of Tree Sparsity in Accelerated MRI", In MICCAI Workshop on Sparsity Techniques in Medical Imaging, STMI'12, Nice, France, October 2012. (Oral Presentation) (Best Paper Award) [CODE]

[051] Chen Chen, Junzhou Huang and Leon Axel, "Accelerated Parallel Magnetic Resonance Imaging with Joint Gradient and Wavelet Sparsity", In MICCAI Workshop on Sparsity Techniques in Medical Imaging, STMI'12, Nice, France, October 2012. [CODE]

[050] Xinyi Cui, Shaoting Zhang, Yiqiang Zhan, Mingchen Gao, Junzhou Huang and Dimitris Metaxas, "3D Anatomical Shape Atlas Construction using Mesh Quality Preserved Deformable Models", In MICCAI Workshop on Mesh Processing in Medical Image Analysis, MeshMed'12, Nice, France, October 2012.

[049] Xinyi Cui, Junzhou Huang, Shaoting Zhang and Dimitris Metaxas, "Background Subtraction using Group Sparsity and Low Rank Constraint", In Proc. of the 12th European Conference on Computer Vision, ECCV'12, Firenze, Italy, October 2012.

[048] Fei Yang, Junzhou Huang, Xiang Yu, Dimitris Metaxas, "Robust Face Tracking with a Consumer Depth Camera", IEEE International Conference on Image Processing, ICIP'12, Orlando, Florida, USA, September 2012.

[047] Fei Yang, Xiang Yu, Junzhou Huang, Peng Yang, Dimitris Metaxas, "Robust Eyelid Tracking for Fatigue Detection", IEEE International Conference on Image Processing, ICIP'12, Orlando, Florida, USA, September 2012.

[046] Lin Zhong, Qingshan Liu, Peng Yang, Bo Liu, Junzhou Huang and Dimitris Metaxas, "Learning Active Facial Patches for Expression Analysis". In Proc. of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'12, Providence, Rhode Island, USA, June 2012.

[045] Xinyi Cui, Shaoting Zhang, Junzhou Huang, Xiaolei Huang, Dimitris Metaxas, Leon Axel, "Left Endocardium Segmentation using Spatio-temporal Metamorphs". IEEE International Symposium on Biomedical Imaging, ISBI'12, Barcelona, Spain, May 2012.

[044] Junzhou Huang, Fei Yang, "Compressed Magnetic Resonace Imaging Based on Wavelet Sparsity and Nonlocal Total Variation". IEEE International Symposium on Biomedical Imaging, ISBI'12, Barcelona, Spain, May 2012. [CODE]

[043] Shaoting Zhang, Junzhou Huang, Hongsheng Li and Dimitris Metaxas, "Automatic Image Annotation and Retrieval Using Group Sparsity". IEEE Transactions on Systems, Man, and Cybernetics: Part B (TSMC), Volume 42, Issue 3, pp. 838-849, June 2012. [CODE]

[042] Shaoting Zhang, Yiqiang Zhan, Maneesh Dewan, Junzhou Huang, Dimitris Metaxas and Xiang Zhou, "Towards Robust and Effective Shape Modeling: Sparse Shape Composition". Medical Image Analysis, Volume 16, Issue 1, pp. 265-277, January 2012. [CODE]

2011

[041] Junzhou Huang, Tong Zhang and Dimitris Metaxas."Learning With Structured Sparsity", Journal of Machine Learning Research, Volume 12, pp. 3371-3412, November 2011. (Tech Report arXiv:0903.3002, March 2009). [CODE]

[040] Junzhou Huang, Shaoting Zhang, Hongsheng Li, Dimitris Metaxas, "Composite Splitting Algorithms for Convex Optimization", Computer Vision and Image Understanding, Volume 115, Number 12, pp. 1610-1622, December 2011. [CODE]

[039] Junzhou Huang, Shaoting Zhang, Dimitris Metaxas, "Efficient MR Image Reconstruction for Compressed MR Imaging", Medical Image Analysis, Volume 15, Issue 5, pp. 670-679, October 2011. [CODE]

[038] Athina P. Petropulu, Yao Yu and Junzhou Huang, "On Exploring Sparsity in Widely Separated MIMO Radar". In Proc. of Asilomar Conference on Signals, Systems & Computers, Asilomar'11, November 2011.

[037] Hongsheng Li, Junzhou Huang, Shaoting Zhang, and Xiaolei Huang, "Optimal Object Matching via Convexification and Composition", In Proc. of the 13th International Conference on Computer Vision, ICCV'11, Barcelona, Spain, November 2011. [video 1] [video 2] [video 3] [video 4]

[036] Tian Shen, Xiaoleo Huang, Hongsheng Li, Edward Kim, Shaoting Zhang, and Junzhou Huang, "A 3D Laplacian-Driven Parametric Deformable Model", In Proc. of the 13th International Conference on Computer Vision, ICCV'11, Barcelona, Spain, November 2011.

[035] Shaoting Zhang, Junzhou Huang, Mustafa Uzunbas, Tian Shen, Foteini Delis, Xiaolei Huang, Nora Volkow, Panayotis Thanos and Dimitris N. Metaxas, "3D Segmentation of Rodent Brain Structures Using Hierarchical Shape Priors and Deformable Models", In Proc. of the 14th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'11, Toronto, Canada, September 2011.

[034] Shaoting Zhang, Yiqiang Zhan, Maneesh Dewan, Junzhou Huang, Dimitris Metaxas and Xiang Zhou, "Deformable Segmentation via Sparse Shape Composition: Towards the Robustness to Weak Appearance Cues", In Proc. of the 14th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'11, Toronto, Canada, September 2011. (MICCAI Young Scientist Award Runners Up)

[033] Baiyang Liu, Junzhou Huang, Casimir Kulikowski, Lin Yang, "Robust Tracking Using Local Sparse Appearance Model and K-Selection", In Proc. of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'11, Colorado Springs, Colorado, USA, June 2011. Oral presentation.

[032] Shaoting Zhang, Yiqiang Zhan, Maneesh Dewan, Junzhou Huang, Dimitris Metaxas and Xiang Zhou, "Sparse Shape Composition: A New Framework for Shape Prior Modeling", In Proc. of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'11, Colorado Springs, Colorado, USA, June 2011.

[031] Mingchen Gao, Junzhou Huang, Shaoting Zhang, Zhen Qian, Szilard Voros, Dimitri Metaxas, Leon Axel, "4D Cardiac Reconstruction Using High Resolution CT Images", In Proc. of the 6th International Conference on Functional Imaging and Modeling of the Heart, FIMH'11, New York, USA, May 2011. (Oral presentation). (Best Paper Award)

[030] Shaoting Zhang, Mustafa Uzunbas, Zhennan Yan, Mingchen Gao, Junzhou Huang, Dimitri Metaxas, Leon Axel, "Construction of Left Ventricle 3D Shape Atlas from Cardiac MRI", In Proc. of the 6th International Conference on Functional Imaging and Modeling of the Heart, FIMH'11, New York, USA, May 2011.

[029] Shaoting Zhang, Junzhou Huang, Mustafa Uzunbas, Tian Shen, Foteini Delis, Xiaolei Huang, Nora Volkow, Panayotis Thanos, Dimitris Metaxas, "3D Segmentation of Rodent Brain Structures Using Active Volume Model With Shape Priors", In Proc. of IEEE Int'l Symposium on Biomedical Imaging: From Nano to Macro, ISBI’11, Chicago, Illinois, USA, March 2011. Oral presentation.

[028] Yang Yu, Junzhou Huang, Shaoting Zhang, Christophe Restif, Xiaolei Huang, Dimitris Metaxas, "Group Sparsity Based Classification for Cervigram Segmentation", In Proc. of IEEE Int'l Symposium on Biomedical Imaging: From Nano to Macro, ISBI’11, Chicago, Illinois, USA, March 2011.

[027] Fei Yang, Junzhou Huang, Dimitris Metaxas, "Sparse Shape Registration for Occluded Facial Feature Localization", In Proc. of the 9th Conference on Automatic Face and Gesture Recognition, FG'11, Santa Barbara, California, USA, March 2011.

[026] Fei Yang, Junzhou Huang, Peng Yang, Dimitris Metaxas, "Eye Localization through Multiscale Sparse Dictionaries", In Proc. the 9th Conference on Automatic Face and Gesture Recognition, FG' 11, Santa Barbara, California, USA, March 2011.

[025] Shaoting Zhang, Junzhou Huang and Dimitris Metaxas, "Robust Mesh Editing Using Laplacian Coordinates", Graphical Models, Volume 73, Issue 1, pp.10-19, January, 2011. [CODE]

2010

[024] Junzhou Huang, Shaoting Zhang and Dimitris Metaxas. " Efficient MR Image Reconstruction for Compressed MR Imaging ", In Proc. of the 13th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'10, Beijing, China, Septerm 2010. Oral presentation. MICCAI Young Scientist Award. [CODE]

[023] Baiyang Liu, Lin Yang, Junzhou Huang, Peter Meer, Leiguang Gong, Casimir Kulikowski, ”Robust and Fast Collaborative Tracking with Two Stage Sparse Optimization”, In Proc. of the 11th European Conference on Computer Vision, ECCV'10, Crete, Greece, September 2010.

[022] Junzhou Huang, Shaoting Zhang and Dimitris Metaxas. " Fast Optimization for Mixture Prior Models ", In Proc. of the 11th European Conference on Computer Vision, ECCV'10, Crete, Greece, September 2010. [CODE]

[020] Tian Shen, Shaoting Zhang, Junzhou Huang, Xiaolei Huang and Dimitris Metaxas, "Integrating Shape and Texture in 3D Deformable Models: From Metamorphs to Active Volume Models", book chapter, to appear in Multi Modality State-of-the-Art Medical Image Segmentation and Registration Methodologies, Springer, 2010.

[019] Shaoting Zhang, Junzhou Huang,Yuchi Huang, Yang Yu, Hongsheng Li, Dimitris Metaxas, "Automatic Image Annotation Using Group Sparsity", In Proc. of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'10, San Francisco, USA, June 2010. Oral presentation. [CODE]

[018] Shaoting Zhang, Junzhou Huang, Wei Wang, Xiaolei Huang, Dimitris Metaxas, "Cervigram Image Segmentation Based on Reconstructive Sparse Representations", In Proc. of SPIE, Medical Imaging: Image Processing, San Diego, USA, February 2010. Oral presentation. [Slides]

[017] Shaoting Zhang, Junzhou Huang, Wei Wang, Xiaolei Huang, Dimitris Metaxas, "Discriminative Sparse Representations for Cervigram Image Segmentation", In Proc. of IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'10, Rotterdam, Netherlands, April 2010.

2009

[016] Junzhou Huang, Tong Zhang, Dimitris Metaxas, "Learning with Structured Sparsity", In Proc. of the 26th International Conference on Machine Learning, ICML'09, Montreal, Quebec, Canada, June 2009. Oral presentation. [Slides] [CODE]

[015] Junzhou Huang, Xiaolei Huang, Dimitris Metaxas, "Learning with Dynamic Group Sparsity", In Proc. of the 12th International Conference on Computer Vision, ICCV'09, Kyoto, Japan, October 2009. Oral presentation. [Slides] [CODE]

2008

[014] Junzhou Huang, Zhen Qian, Xiaolei Huang, Dimitris Metaxas, Leon Axel, "Tag Separation in Cardiac Tagged MRI", In Proc. of the 11th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'08, New York, USA, September 2008.

[013] Tian Shen, Yaoyao Zhu, Xiaolei Huang, Junzhou Huang, Dimitris Metaxas, Leon Axel, "Active Volume Models with Probabilistic Object Boundary Prediction Module", In Proc. of the 11th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'08, New York, USA, September 2008.

[012] Junzhou Huang, Xiaolei Huang, Dimitris Metaxas, "Simultaneous Image Transformation and Sparse Representation Recovery", In Proc. of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'08, Anchorage, AL, USA, June 2008. [CODE]

2007

[011] Junzhou Huang, Xiaolei Huang, Dimitris Metaxas, "Optimization and Learning for Registration of Moving Dynamic Textures", In Proc. of the 11th International Conference on Computer Vision, ICCV'07, Rio de Janeiro, Brazil, October 2007. Oral presentation.[Slides]

[010] Junzhou Huang, Xiaolei Huang, Dimitris Metaxas, and Leon Axel, "Adaptive Metamorphs Model for 3D Medical Image Segmentation", In Proc. of the 10th Annual International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI'07, pp. 302-310, Brisbane, Australia, October 2007.

[009] Junzhou Huang, Xiaolei Huang, Dimitris Metaxas, Leon Axel, "Dynamic Texture Based Heart Location and Segmentation in 4-D Cardiac Images" , In Proc. of IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'07, pp. 852-855, Washington DC, USA, April 2007.

2006

[008] Junzhou Huang, Xiaolei Huang, Dimitris Metaxas, Debarata Banerjee, "3D Tumor Shape Reconstruction from 2D Bioluminescence Images and Registration with CT Images", In Proc. of the 1st Workshop on Microscopic Image Analysis with Applications in Biology, MIAAB'06, Arlington, Virginia, USA, April 2006. Oral presentation.

[007] Junzhou Huang, Xiaolei Huang, Dimitris Metaxas, Debarata Banerjee, "3D Tumor Shape Reconstruction from 2D Bioluminescence Images" , In Proc. of IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'06, pp. 606-609, Arlington, Virginia, USA, April 2006. Oral presentation.

2005

[006] Junzhou Huang, Tieniu Tan, Li Ma, Yunhong Wang, "Phase Correlation Based Iris Image Registration Model", Journal of Computer Science and Technology, Vol. 20, No. 2, pp. 419-425, March 2005.

2004

[005] Junzhou Huang , Yunhong Wang, Jiali Cui, Tieniu Tan, "Noise Removal and Impainting Model for Iris Image", In Proc. of International Conference on Image Processing, ICIP'04, pp. 869-872, October 2004.

[004] Junzhou Huang, Yunhong Wang, Tieniu Tan, Jiali Cui, "A New Iris Segmentation Method for Recognition", In Proc. of the 17th International Conference on Pattern Recognition, ICPR'04 (3), pp. 554-557, August 2004.

[003] Jiali Cui, Yunhong Wang, Junzhou Huang, Tieniu Tan, Zenan Sun, "An Iris Image Synthesis Method Based on PCA and Super-Resolution", In Proc. of the 17th International Conference on Pattern Recognition, ICPR'04 (4), pp. 471-474, August 2004.

[002] Junzhou Huang, Li Ma, and Yunhong Wang and Tieniu Tan, "Iris Recognition Based on Local Orientation Description", In Proc. of Asian Conference on Computer Vision, ACCV'04, pp. 954-959, Korea, January 2004.

2003

[001] Junzhou Huang, Li Ma, Tieniu Tan and Yunhong Wang, "Learning-based Resolution Enhancement of Iris Images", In Proc. of the 14th British Machine Vision Conference, BMVC'03, pp. 153-162, Norwich, U.K., September 2003.

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