Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Networks. - Sitao Luan; Mingde Zhao 001; Chenqing Hua; Xiao-Wen Chang; Doina Precup (CoRR, 2020)

Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification? - Sitao Luan; Chenqing Hua; Qincheng Lu; Jiaqi Zhu; Mingde Zhao 001; Shuyuan Zhang; Xiao-Wen Chang; Doina Precup (CoRR, 2021)

High-Order Pooling for Graph Neural Networks with Tensor Decomposition. - Chenqing Hua; Guillaume Rabusseau; Jian Tang (NeurIPS, 2022)

Revisiting Heterophily For Graph Neural Networks. - Sitao Luan; Chenqing Hua; Qincheng Lu; Jiaqi Zhu; Mingde Zhao 001; Shuyuan Zhang; Xiao-Wen Chang; Doina Precup (NeurIPS, 2022)

Graph Neural Networks Intersect Probabilistic Graphical Models: A Survey. - Chenqing Hua (CoRR, 2022)

When Do We Need GNN for Node Classification? - Sitao Luan; Chenqing Hua; Qincheng Lu; Jiaqi Zhu; Xiao-Wen Chang; Doina Precup (CoRR, 2022)

Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Neural Networks. - Sitao Luan; Mingde Zhao 001; Chenqing Hua; Xiao-Wen Chang; Doina Precup (CoRR, 2022)

When Do We Need Graph Neural Networks for Node Classification? - Sitao Luan; Chenqing Hua; Qincheng Lu; Jiaqi Zhu; Xiao-Wen Chang; Doina Precup (COMPLEX NETWORKS (1), 2023)

MUDiff: Unified Diffusion for Complete Molecule Generation. - Chenqing Hua; Sitao Luan; Minkai Xu; Zhitao Ying; Jie Fu; Stefano Ermon; Doina Precup (LoG, 2023)

When Do Graph Neural Networks Help with Node Classification? Investigating the Homophily Principle on Node Distinguishability. - Sitao Luan; Chenqing Hua; Minkai Xu; Qincheng Lu; Jiaqi Zhu; Xiao-Wen Chang; Jie Fu; Jure Leskovec; Doina Precup (NeurIPS, 2023)

ReactZyme: A Benchmark for Enzyme-Reaction Prediction. - Chenqing Hua; Bozitao Zhong; Sitao Luan; Liang Hong; Guy Wolf; Doina Precup; Shuangjia Zheng (NeurIPS, 2024)

Effective Protein-Protein Interaction Exploration with PPIretrieval. - Chenqing Hua; Connor W. Coley; Guy Wolf; Doina Precup; Shuangjia Zheng (CoRR, 2024)

Deep Geometry Handling and Fragment-wise Molecular 3D Graph Generation. - Odin Zhang; Yufei Huang 002; Shichen Cheng; Mengyao Yu; Xujun Zhang; Haitao Lin; Yundian Zeng; Mingyang Wang 004; Zhenxing Wu; Huifeng Zhao; Zaixi Zhang; Chenqing Hua; et al. (CoRR, 2024)

The Heterophilic Graph Learning Handbook: Benchmarks, Models, Theoretical Analysis, Applications and Challenges. - Sitao Luan; Chenqing Hua; Qincheng Lu; Liheng Ma; Lirong Wu; Xinyu Wang; Minkai Xu; Xiao-Wen Chang; Doina Precup; Rex Ying; Stan Z. Li; Jian Tang 005; et al. (CoRR, 2024)

Are Heterophily-Specific GNNs and Homophily Metrics Really Effective? Evaluation Pitfalls and New Benchmarks. - Sitao Luan; Qincheng Lu; Chenqing Hua; Xinyu Wang; Jiaqi Zhu; Xiao-Wen Chang; Guy Wolf; Jian Tang 005 (CoRR, 2024)

EnzymeFlow: Generating Reaction-specific Enzyme Catalytic Pockets through Flow Matching and Co-Evolutionary Dynamics. - Chenqing Hua; Yong Liu; Dinghuai Zhang; Odin Zhang; Sitao Luan; Kevin K. Yang; Guy Wolf; Doina Precup; Shuangjia Zheng (CoRR, 2024)

Learning From Graph-Structured Data: Addressing Design Issues and Exploring Practical Applications in Graph Representation Learning. - Chenqing Hua (CoRR, 2024)

Reaction-conditioned De Novo Enzyme Design with GENzyme. - Chenqing Hua; Jiarui Lu; Yong Liu; Odin Zhang; Jian Tang 005; Rex Ying; Wengong Jin; Guy Wolf; Doina Precup; Shuangjia Zheng (CoRR, 2024)

Graph Neural Networks Meet Probabilistic Graphical Models: A Survey. - Chenqing Hua; Sitao Luan; Qian Zhang; Jie Fu; Guy Wolf (ICASSP, 2025)