Wang, Yu Guang

17 publications

NeurIPS 2025 How Particle System Theory Enhances Hypergraph Message Passing Yixuan Ma, Kai Yi, Pietro Lio, Shi Jin, Yu Guang Wang

ICMLW 2024 GROD: Enhancing Generalization of Transformer with Out-of-Distribution Detection Yijin Zhou, Yu Guang Wang

ICML 2024 How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-Smoothing, and Over-Squashing Keke Huang, Yu Guang Wang, Ming Li, Pietro Lio

NeurIPSW 2024 Improving Antibody Design with Force-Guided Sampling in Diffusion Models Paulina Kulytė, Francisco Vargas, Simon V Mathis, Yu Guang Wang, José Miguel Hernández-Lobato, Pietro Lio

TMLR 2024 Layer-Diverse Negative Sampling for Graph Neural Networks Wei Duan, Jie Lu, Yu Guang Wang, Junyu Xuan

ICMLW 2024 Path Complex Neural Network for Molecular Property Prediction Longlong Li, Xiang Liu, Guanghui Wang, Yu Guang Wang, Kelin Xia

ICLR 2023 ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks Yuelin Wang, Kai Yi, Xinliang Liu, Yu Guang Wang, Shi Jin

CVPR 2023 EqMotion: Equivariant Multi-Agent Motion Prediction with Invariant Interaction Reasoning Chenxin Xu, Robby T. Tan, Yuhong Tan, Siheng Chen, Yu Guang Wang, Xinchao Wang, Yanfeng Wang

ICML 2023 How Powerful Are Shallow Neural Networks with Bandlimited Random Weights? Ming Li, Sho Sonoda, Feilong Cao, Yu Guang Wang, Jiye Liang

NeurIPSW 2022 ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks Yuelin Wang, Kai Yi, Xinliang Liu, Yu Guang Wang, Shi Jin

JMLR 2022 Decimated Framelet System on Graphs and Fast G-Framelet Transforms Xuebin Zheng, Bingxin Zhou, Yu Guang Wang, Xiaosheng Zhuang

LoG 2022 Well-Conditioned Spectral Transforms for Dynamic Graph Representation Bingxin Zhou, Xinliang Liu, Yuehua Liu, Yunying Huang, Pietro Lio, Yu Guang Wang

ICLRW 2021 Grassmann Graph Embedding Bingxin Zhou, Xuebin Zheng, Yu Guang Wang, Ming Li, Junbin Gao

ICLRW 2021 Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang, Nina Otter, Guido Montufar, Pietro Liò, Michael M. Bronstein

NeurIPSW 2020 Can Neural Networks Learn Persistent Homology Features? Guido Montufar, Nina Otter, Yu Guang Wang

ICML 2020 Haar Graph Pooling Yu Guang Wang, Ming Li, Zheng Ma, Guido Montufar, Xiaosheng Zhuang, Yanan Fan

NeurIPS 2020 Path Integral Based Convolution and Pooling for Graph Neural Networks Zheng Ma, Junyu Xuan, Yu Guang Wang, Ming Li, Pietro Liò