Rong, Yu

46 publications

ICLR 2025 Atomas: Hierarchical Adaptive Alignment on Molecule-Text for Unified Molecule Understanding and Generation Yikun Zhang, Geyan Ye, Chaohao Yuan, Bo Han, Long-Kai Huang, Jianhua Yao, Wei Liu, Yu Rong

ICLR 2025 CirT: Global Subseasonal-to-Seasonal Forecasting with Geometry-Inspired Transformer Yang Liu, Zinan Zheng, Jiashun Cheng, Fugee Tsung, Deli Zhao, Yu Rong, Jia Li

ICLRW 2025 Flow Along the K-Amplitude for Generative Modeling Weitao Du, Shuning Chang, Jiasheng Tang, Yu Rong, Fan Wang, Shengchao Liu

ICML 2025 IBCircuit: Towards Holistic Circuit Discovery with Information Bottleneck Tian Bian, Yifan Niu, Chaohao Yuan, Chengzhi Piao, Bingzhe Wu, Long-Kai Huang, Yu Rong, Tingyang Xu, Hong Cheng, Jia Li

ICLR 2025 InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization Yifan Niu, Ziqi Gao, Tingyang Xu, Yang Liu, Yatao Bian, Yu Rong, Junzhou Huang, Jia Li

CVPR 2025 LUCAS: Layered Universal Codec Avatars Di Liu, Teng Deng, Giljoo Nam, Yu Rong, Stanislav Pidhorskyi, Junxuan Li, Jason Saragih, Dimitris N. Metaxas, Chen Cao

ICML 2025 Large Language-Geometry Model: When LLM Meets Equivariance Zongzhao Li, Jiacheng Cen, Bing Su, Tingyang Xu, Yu Rong, Deli Zhao, Wenbing Huang

NeurIPS 2025 MOF-BFN: Metal-Organic Frameworks Structure Prediction via Bayesian Flow Networks Rui Jiao, Hanlin Wu, Wenbing Huang, Yuxuan Song, Yawen Ouyang, Yu Rong, Tingyang Xu, Pengju Wang, Hao Zhou, Wei-Ying Ma, Jingjing Liu, Yang Liu

ICLR 2025 MolSpectra: Pre-Training 3D Molecular Representation with Multi-Modal Energy Spectra Liang Wang, Shaozhen Liu, Yu Rong, Deli Zhao, Qiang Liu, Shu Wu, Liang Wang

NeurIPS 2025 Non-Stationary Equivariant Graph Neural Networks for Physical Dynamics Simulation Chaohao Yuan, Maoji Wen, Ercan Engin Kuruoglu, Yang Liu, Jia Li, Tingyang Xu, Deli Zhao, Hong Cheng, Yu Rong

NeurIPS 2025 Scaling Language-Centric Omnimodal Representation Learning Chenghao Xiao, Hou Pong Chan, Hao Zhang, Weiwen Xu, Mahani Aljunied, Yu Rong

NeurIPS 2025 The Rise of Parameter Specialization for Knowledge Storage in Large Language Models Yihuai Hong, Yiran Zhao, Wei Tang, Yang Deng, Yu Rong, Wenxuan Zhang

NeurIPS 2025 Universally Invariant Learning in Equivariant GNNs Jiacheng Cen, Anyi Li, Ning Lin, Tingyang Xu, Yu Rong, Deli Zhao, Zihe Wang, Wenbing Huang

TMLR 2024 Equivariant Graph Learning for High-Density Crowd Trajectories Modeling Yang Liu, Zinan Zheng, Yu Rong, Jia Li

ICLR 2024 Neural Atoms: Propagating Long-Range Interaction in Molecular Graphs Through Efficient Communication Channel Xuan Li, Zhanke Zhou, Jiangchao Yao, Yu Rong, Lu Zhang, Bo Han

ICLR 2024 SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases Yang Liu, Jiashun Cheng, Haihong Zhao, Tingyang Xu, Peilin Zhao, Fugee Tsung, Jia Li, Yu Rong

NeurIPS 2023 Deep Insights into Noisy Pseudo Labeling on Graph Data Botao Wang, Jia Li, Yang Liu, Jiashun Cheng, Yu Rong, Wenjia Wang, Fugee Tsung

AAAI 2023 DrugOOD: Out-of-Distribution Dataset Curator and Benchmark for AI-Aided Drug Discovery - A Focus on Affinity Prediction Problems with Noise Annotations 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, Yatao Bian

AAAI 2023 Energy-Motivated Equivariant Pretraining for 3D Molecular Graphs Rui Jiao, Jiaqi Han, Wenbing Huang, Yu Rong, Yang Liu

NeurIPS 2023 Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics Liming Wu, Zhichao Hou, Jirui Yuan, Yu Rong, Wenbing Huang

AAAI 2023 Human Mobility Modeling During the COVID-19 Pandemic via Deep Graph Diffusion Infomax Yang Liu, Yu Rong, Zhuoning Guo, Nuo Chen, Tingyang Xu, Fugee Tsung, Jia Li

NeurIPSW 2023 Long-Range Neural Atom Learning for Molecular Graphs Xuan Li, Zhanke Zhou, Jiangchao Yao, Yu Rong, Lu Zhang, Bo Han

TMLR 2023 Noise-Robust Graph Learning by Estimating and Leveraging Pairwise Interactions Xuefeng Du, Tian Bian, Yu Rong, Bo Han, Tongliang Liu, Tingyang Xu, Wenbing Huang, Yixuan Li, Junzhou Huang

ICLRW 2022 Diversified Multiscale Graph Learning with Graph Self-Correction Yuzhao Chen, Yatao Bian, Jiying Zhang, Xi Xiao, Tingyang Xu, Yu Rong

ICLR 2022 Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning Yatao Bian, Yu Rong, Tingyang Xu, Jiaxiang Wu, Andreas Krause, Junzhou Huang

NeurIPS 2022 Equivariant Graph Hierarchy-Based Neural Networks Jiaqi Han, Wenbing Huang, Tingyang Xu, Yu Rong

NeurIPSW 2022 Equivariant Graph Hierarchy-Based Neural Networks Jiaqi Han, Yu Rong, Tingyang Xu, Wenbing Huang

ICLR 2022 Equivariant Graph Mechanics Networks with Constraints Wenbing Huang, Jiaqi Han, Yu Rong, Tingyang Xu, Fuchun Sun, Junzhou Huang

IJCAI 2022 Fine-Tuning Graph Neural Networks via Graph Topology Induced Optimal Transport Jiying Zhang, Xi Xiao, Long-Kai Huang, Yu Rong, Yatao Bian

ICML 2022 Frustratingly Easy Transferability Estimation Long-Kai Huang, Junzhou Huang, Yu Rong, Qiang Yang, Ying Wei

ICML 2022 Local Augmentation for Graph Neural Networks Songtao Liu, Rex Ying, Hanze Dong, Lanqing Li, Tingyang Xu, Yu Rong, Peilin Zhao, Junzhou Huang, Dinghao Wu

CVPR 2022 Towards Diverse and Natural Scene-Aware 3D Human Motion Synthesis Jingbo Wang, Yu Rong, Jingyuan Liu, Sijie Yan, Dahua Lin, Bo Dai

ICCV 2021 Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentation Jinyu Yang, Chunyuan Li, Weizhi An, Hehuan Ma, Yuzhi Guo, Yu Rong, Peilin Zhao, Junzhou Huang

ICCVW 2021 FrankMocap: A Monocular 3D Whole-Body Pose Estimation System via Regression and Integration Yu Rong, Takaaki Shiratori, Hanbyul Joo

ICLR 2021 Graph Information Bottleneck for Subgraph Recognition Junchi Yu, Tingyang Xu, Yu Rong, Yatao Bian, Junzhou Huang, Ran He

AAAI 2021 Hierarchical Graph Capsule Network Jinyu Yang, Peilin Zhao, Yu Rong, Chaochao Yan, Chunyuan Li, Hehuan Ma, Junzhou Huang

ICML 2021 Learning Diverse-Structured Networks for Adversarial Robustness Xuefeng Du, Jingfeng Zhang, Bo Han, Tongliang Liu, Yu Rong, Gang Niu, Junzhou Huang, Masashi Sugiyama

NeurIPS 2021 Not All Low-Pass Filters Are Robust in Graph Convolutional Networks Heng Chang, Yu Rong, Tingyang Xu, Yatao Bian, Shiji Zhou, Xin Wang, Junzhou Huang, Wenwu Zhu

IJCAI 2021 On Self-Distilling Graph Neural Network Yuzhao Chen, Yatao Bian, Xi Xiao, Yu Rong, Tingyang Xu, Junzhou Huang

AAAI 2020 A Restricted Black-Box Adversarial Framework Towards Attacking Graph Embedding Models Heng Chang, Yu Rong, Tingyang Xu, Wenbing Huang, Honglei Zhang, Peng Cui, Wenwu Zhu, Junzhou Huang

NeurIPS 2020 Deep Multimodal Fusion by Channel Exchanging Yikai Wang, Wenbing Huang, Fuchun Sun, Tingyang Xu, Yu Rong, Junzhou Huang

NeurIPS 2020 Dirichlet Graph Variational Autoencoder Jia Li, Jianwei Yu, Jiajin Li, Honglei Zhang, Kangfei Zhao, Yu Rong, Hong Cheng, Junzhou Huang

ICLR 2020 DropEdge: Towards Deep Graph Convolutional Networks on Node Classification Yu Rong, Wenbing Huang, Tingyang Xu, Junzhou Huang

AAAI 2020 Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks Tian Bian, Xi Xiao, Tingyang Xu, Peilin Zhao, Wenbing Huang, Yu Rong, Junzhou Huang

NeurIPS 2020 Self-Supervised Graph Transformer on Large-Scale Molecular Data Yu Rong, Yatao Bian, Tingyang Xu, Weiyang Xie, Ying Wei, Wenbing Huang, Junzhou Huang

NeurIPS 2018 Adaptive Sampling Towards Fast Graph Representation Learning Wenbing Huang, Tong Zhang, Yu Rong, Junzhou Huang