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2020 – today
- 2025
[i22]Yilun Zheng, Sha Li, Fangkun Wu, Yang Ziyi, Lin Hongchao, Zhichao Hu, Cai Xinjun, Ziming Wang, Jinxuan Chen, Sitao Luan, Jiahao Xu, Lihui Chen:
FanChuan: A Multilingual and Graph-Structured Benchmark For Parody Detection and Analysis. CoRR abs/2502.16503 (2025)- 2024
- [c11]Qincheng Lu, Sitao Luan, Xiao-Wen Chang:
GCEPNet: Graph Convolution-Enhanced Expectation Propagation for Massive MIMO Detection. GLOBECOM 2024: 444-449 - [c10]Chenqing Hua, Bozitao Zhong, Sitao Luan, Liang Hong, Guy Wolf, Doina Precup, Shuangjia Zheng:
ReactZyme: A Benchmark for Enzyme-Reaction Prediction. NeurIPS 2024 - [c9]Yilun Zheng, Sitao Luan, Lihui Chen:
What Is Missing For Graph Homophily? Disentangling Graph Homophily For Graph Neural Networks. NeurIPS 2024 - [i21]Qincheng Lu, Jiaqi Zhu, Sitao Luan, Xiao-Wen Chang:
Representation Learning on Heterophilic Graph with Directional Neighborhood Attention. CoRR abs/2403.01475 (2024) - [i20]Qincheng Lu, Sitao Luan, Xiao-Wen Chang:
GCEPNet: Graph Convolution-Enhanced Expectation Propagation for Massive MIMO Detection. CoRR abs/2404.14886 (2024) - [i19]Yilun Zheng, Sitao Luan, Lihui Chen:
What Is Missing In Homophily? Disentangling Graph Homophily For Graph Neural Networks. CoRR abs/2406.18854 (2024) - [i18]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, Guy Wolf, Stefanie Jegelka:
The Heterophilic Graph Learning Handbook: Benchmarks, Models, Theoretical Analysis, Applications and Challenges. CoRR abs/2407.09618 (2024) - [i17]Chenqing Hua, Bozitao Zhong, Sitao Luan, Liang Hong, Guy Wolf, Doina Precup, Shuangjia Zheng:
Reactzyme: A Benchmark for Enzyme-Reaction Prediction. CoRR abs/2408.13659 (2024) - [i16]Sitao Luan, Qincheng Lu, Chenqing Hua, Xinyu Wang, Jiaqi Zhu, Xiao-Wen Chang, Guy Wolf, Jian Tang:
Are Heterophily-Specific GNNs and Homophily Metrics Really Effective? Evaluation Pitfalls and New Benchmarks. CoRR abs/2409.05755 (2024) - [i15]Qincheng Lu, Jiaqi Zhu, Sitao Luan, Xiao-Wen Chang:
Flexible Diffusion Scopes with Parameterized Laplacian for Heterophilic Graph Learning. CoRR abs/2409.09888 (2024) - [i14]Chenqing Hua, Yong Liu, Dinghuai Zhang, Odin Zhang, Sitao Luan, Kevin K. Yang, Guy Wolf, Doina Precup, Shuangjia Zheng:
EnzymeFlow: Generating Reaction-specific Enzyme Catalytic Pockets through Flow Matching and Co-Evolutionary Dynamics. CoRR abs/2410.00327 (2024) - [i13]Yilun Zheng, Xiang Li, Sitao Luan, Xiaojiang Peng, Lihui Chen:
Is Graph Convolution Always Beneficial For Every Feature? CoRR abs/2411.07663 (2024) - [i12]Yilun Zheng, Zhuofan Zhang, Ziming Wang, Xiang Li, Sitao Luan, Xiaojiang Peng, Lihui Chen:
Rethinking Structure Learning For Graph Neural Networks. CoRR abs/2411.07672 (2024) - 2023
- [c8]Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Xiao-Wen Chang, Doina Precup:
When Do We Need Graph Neural Networks for Node Classification? COMPLEX NETWORKS (1) 2023: 37-48 - [c7]Sitao Luan, Mingde Zhao, Xiao-Wen Chang, Doina Precup:
Training Matters: Unlocking Potentials of Deeper Graph Convolutional Neural Networks. COMPLEX NETWORKS (1) 2023: 49-60 - [c6]Chenqing Hua, Sitao Luan, Minkai Xu, Zhitao Ying, Jie Fu, Stefano Ermon, Doina Precup:
MUDiff: Unified Diffusion for Complete Molecule Generation. LoG 2023: 33 - [c5]Sitao Luan, Chenqing Hua, Minkai Xu, Qincheng Lu, Jiaqi Zhu, Xiao-Wen Chang, Jie Fu, Jure Leskovec, Doina Precup:
When Do Graph Neural Networks Help with Node Classification? Investigating the Homophily Principle on Node Distinguishability. NeurIPS 2023 - [i11]Sitao Luan, Chenqing Hua, Minkai Xu, Qincheng Lu, Jiaqi Zhu, Xiao-Wen Chang, Jie Fu, Jure Leskovec, Doina Precup:
When Do Graph Neural Networks Help with Node Classification: Investigating the Homophily Principle on Node Distinguishability. CoRR abs/2304.14274 (2023) - [i10]Chenqing Hua, Sitao Luan, Minkai Xu, Rex Ying, Jie Fu, Stefano Ermon, Doina Precup:
MUDiff: Unified Diffusion for Complete Molecule Generation. CoRR abs/2304.14621 (2023) - [i9]Sitao Luan:
On Addressing the Limitations of Graph Neural Networks. CoRR abs/2306.12640 (2023) - 2022
- [c4]Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Mingde Zhao, Shuyuan Zhang, Xiao-Wen Chang, Doina Precup:
Revisiting Heterophily For Graph Neural Networks. NeurIPS 2022 - [i8]Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Mingde Zhao, Shuyuan Zhang, Xiao-Wen Chang, Doina Precup:
Revisiting Heterophily For Graph Neural Networks. CoRR abs/2210.07606 (2022) - [i7]Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Xiao-Wen Chang, Doina Precup:
When Do We Need GNN for Node Classification? CoRR abs/2210.16979 (2022) - [i6]Sitao Luan, Mingde Zhao, Chenqing Hua, Xiao-Wen Chang, Doina Precup:
Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Neural Networks. CoRR abs/2212.10822 (2022) - 2021
- [c3]Mingde Zhao, Zhen Liu, Sitao Luan, Shuyuan Zhang, Doina Precup, Yoshua Bengio:
A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning. NeurIPS 2021: 1569-1581 - [i5]Mingde Zhao, Zhen Liu, Sitao Luan, Shuyuan Zhang, Doina Precup, Yoshua Bengio:
A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning. CoRR abs/2106.02097 (2021) - [i4]Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Mingde Zhao, Shuyuan Zhang, Xiao-Wen Chang, Doina Precup:
Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification? CoRR abs/2109.05641 (2021) - 2020
- [c2]Mingde Zhao, Sitao Luan, Ian Porada, Xiao-Wen Chang, Doina Precup:
META-Learning State-based Eligibility Traces for More Sample-Efficient Policy Evaluation. AAMAS 2020: 1647-1655 - [i3]Sitao Luan, Mingde Zhao, Xiao-Wen Chang, Doina Precup:
Training Matters: Unlocking Potentials of Deeper Graph Convolutional Neural Networks. CoRR abs/2008.08838 (2020) - [i2]Sitao Luan, Mingde Zhao, Chenqing Hua, Xiao-Wen Chang, Doina Precup:
Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Networks. CoRR abs/2008.08844 (2020)
2010 – 2019
- 2019
- [c1]Sitao Luan, Mingde Zhao, Xiao-Wen Chang, Doina Precup:
Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks. NeurIPS 2019: 10943-10953 - [i1]Sitao Luan, Xiao-Wen Chang, Doina Precup:
Revisit Policy Optimization in Matrix Form. CoRR abs/1909.09186 (2019)
Coauthor Index
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