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Deep Graph Learning: Algorithms and Applications

It is alway challenging to develop effective machine learning algorithms to efficiently process graph data due to highly complex but inforative graph structure. The goal of this project is to attach this challenge by developing novel deep learning models to effectively and efficiently process graph data.

Figure 1. graph data examples

Publication

  1. 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]
  2. 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]
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. Yu Rong, Yatao Bian, Tingyang Xu, Weiyang Xie, Ying Wei, Wenbing Huang and Junzhou Huang, "GROVER: Self-Supervised Message Passing Transformer on Largescale Molecular Graphs", In Proc. of the 34th Annual Conference on Neural Information Processing Systems, NIPS’20, Vancouver, Canada, December 2020.
  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. 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.
  21. 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.
  22. 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.
  23. 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.
  24. 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.
  25. 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.
  26. 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.
  27. 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.
  28. 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.
  29. 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.
  30. 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.
  31. 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.
  32. 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.
  33. 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.
  34. 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.
  35. 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.
  36. 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.
  37. 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.
  38. 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.