Ji, Shuiwang

83 publications

FnTML 2025 Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Alex Strasser, Haiyang Yu, Yuqing Xie, Xiang Fu, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji

TMLR 2025 Counterfactual Fairness on Graphs: Augmentations, Hidden Confounders, and Identifiability Hongyi Ling, Zhimeng Jiang, Na Zou, Shuiwang Ji

NeurIPS 2025 Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding Xiner Li, Yulai Zhao, Chenyu Wang, Gabriele Scalia, Gökcen Eraslan, Surag Nair, Tommaso Biancalani, Shuiwang Ji, Aviv Regev, Sergey Levine, Masatoshi Uehara

ICML 2025 DiffMS: Diffusion Generation of Molecules Conditioned on Mass Spectra Montgomery Bohde, Mrunali Manjrekar, Runzhong Wang, Shuiwang Ji, Connor W. Coley

ICML 2025 Discovering Physics Laws of Dynamical Systems via Invariant Function Learning Shurui Gui, Xiner Li, Shuiwang Ji

ICLR 2025 Eliminating Position Bias of Language Models: A Mechanistic Approach Ziqi Wang, Hanlin Zhang, Xiner Li, Kuan-Hao Huang, Chi Han, Shuiwang Ji, Sham M. Kakade, Hao Peng, Heng Ji

ICLR 2025 Fragment and Geometry Aware Tokenization of Molecules for Structure-Based Drug Design Using Language Models Cong Fu, Xiner Li, Blake Olson, Heng Ji, Shuiwang Ji

ICML 2025 Geometry Informed Tokenization of Molecules for Language Model Generation Xiner Li, Limei Wang, Youzhi Luo, Carl Edwards, Shurui Gui, Yuchao Lin, Heng Ji, Shuiwang Ji

TMLR 2025 Hierarchical Language Model Design for Interpretable Graph Reasoning Sambhav Khurana, Xiner Li, Shurui Gui, Shuiwang Ji

TMLR 2025 Language Models for Controllable DNA Sequence Design Xingyu Su, Xiner Li, Yuchao Lin, Ziqian Xie, Degui Zhi, Shuiwang Ji

ICLR 2025 Learning to Discover Regulatory Elements for Gene Expression Prediction Xingyu Su, Haiyang Yu, Degui Zhi, Shuiwang Ji

NeurIPS 2025 ML4CFD Competition: Results and Retrospective Analysis Mouadh Yagoubi, David Danan, Milad Leyli-abadi, Jocelyn Ahmed Mazari, Jean-Patrick Brunet, Abbas Kabalan, Fabien Casenave, Yuxin Ma, Giovanni Catalani, Jean Fesquet, Jacob Helwig, Xuan Zhang, Haiyang Yu, Xavier Bertrand, Frédéric Tost, Michael Bauerheim, Joseph Morlier, Shuiwang Ji

ICML 2025 On Explaining Equivariant Graph Networks via Improved Relevance Propagation Hongyi Ling, Haiyang Yu, Zhimeng Jiang, Na Zou, Shuiwang Ji

ICML 2025 Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design Masatoshi Uehara, Xingyu Su, Yulai Zhao, Xiner Li, Aviv Regev, Shuiwang Ji, Sergey Levine, Tommaso Biancalani

NeurIPS 2025 Tensor Decomposition Networks for Fast Machine Learning Interatomic Potential Computations Yuchao Lin, Cong Fu, Zachary Krueger, Haiyang Yu, Maho Nakata, Jianwen Xie, Emine Kucukbenli, Xiaofeng Qian, Shuiwang Ji

NeurIPS 2025 Towards Precision Protein-Ligand Affinity Prediction Benchmark: A Complete and Modification-Aware DAVIS Dataset Ming Hsiu Wu, Ziqian Xie, Shuiwang Ji, Degui Zhi

ICML 2024 A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction Keqiang Yan, Alexandra Saxton, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

ICLR 2024 Active Test-Time Adaptation: Theoretical Analyses and an Algorithm Shurui Gui, Xiner Li, Shuiwang Ji

ICLR 2024 Complete and Efficient Graph Transformers for Crystal Material Property Prediction Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

NeurIPSW 2024 Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decoding Xiner Li, Yulai Zhao, Chenyu Wang, Gabriele Scalia, Gökcen Eraslan, Surag Nair, Tommaso Biancalani, Shuiwang Ji, Aviv Regev, Sergey Levine, Masatoshi Uehara

NeurIPSW 2024 Eliminating Position Bias of Language Models: A Mechanistic Approach Ziqi Wang, Hanlin Zhang, Xiner Li, Kuan-Hao Huang, Chi Han, Shuiwang Ji, Sham M. Kakade, Hao Peng, Heng Ji

TMLR 2024 Empowering GNNs via Edge-Aware Weisfeiler-Leman Algorithm Meng Liu, Haiyang Yu, Shuiwang Ji

ICML 2024 Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency Yuchao Lin, Jacob Helwig, Shurui Gui, Shuiwang Ji

TMLR 2024 Equivariant Graph Network Approximations of High-Degree Polynomials for Force Field Prediction Zhao Xu, Haiyang Yu, Montgomery Bohde, Shuiwang Ji

TMLR 2024 Genetic InfoMax: Exploring Mutual Information Maximization in High-Dimensional Imaging Genetics Studies Yaochen Xie, Ziqian Xie, Sheikh Muhammad Saiful Islam, Degui Zhi, Shuiwang Ji

ICML 2024 Graph Structure Extrapolation for Out-of-Distribution Generalization Xiner Li, Shurui Gui, Youzhi Luo, Shuiwang Ji

NeurIPS 2024 Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation Keqiang Yan, Xiner Li, Hongyi Ling, Kenna Ashen, Carl Edwards, Raymundo Arróyave, Marinka Zitnik, Heng Ji, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

ICLR 2024 On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods Montgomery Bohde, Meng Liu, Alexandra Saxton, Shuiwang Ji

ICML 2024 Position: TrustLLM: Trustworthiness in Large Language Models Yue Huang, Lichao Sun, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Hanchi Sun, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric P. Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Yang Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao

ICLR 2024 SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations Xuan Zhang, Jacob Helwig, Yuchao Lin, Yaochen Xie, Cong Fu, Stephan Wojtowytsch, Shuiwang Ji

LoG 2023 A Latent Diffusion Model for Protein Structure Generation Cong Fu, Keqiang Yan, Limei Wang, Wing Yee Au, Michael Curtis McThrow, Tao Komikado, Koji Maruhashi, Kanji Uchino, Xiaoning Qian, Shuiwang Ji

NeurIPS 2023 A New Perspective on Building Efficient and Expressive 3D Equivariant Graph Neural Networks Weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, Carla P. Gomes, Zhi-Ming Ma

ICLR 2023 Automated Data Augmentations for Graph Classification Youzhi Luo, Michael Curtis McThrow, Wing Yee Au, Tao Komikado, Kanji Uchino, Koji Maruhashi, Shuiwang Ji

ICML 2023 Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian, Shuiwang Ji

ICML 2023 Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

ICLR 2023 Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models Meng Liu, Haoran Liu, Shuiwang Ji

ICML 2023 Graph Mixup with Soft Alignments Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji, Na Zou

ICML 2023 Group Equivariant Fourier Neural Operators for Partial Differential Equations Jacob Helwig, Xuan Zhang, Cong Fu, Jerry Kurtin, Stephan Wojtowytsch, Shuiwang Ji

NeurIPS 2023 Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization Shurui Gui, Meng Liu, Xiner Li, Youzhi Luo, Shuiwang Ji

ICLR 2023 Learning Fair Graph Representations via Automated Data Augmentations Hongyi Ling, Zhimeng Jiang, Youzhi Luo, Shuiwang Ji, Na Zou

ICLR 2023 Learning Hierarchical Protein Representations via Complete 3D Graph Networks Limei Wang, Haoran Liu, Yi Liu, Jerry Kurtin, Shuiwang Ji

NeurIPS 2023 QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

LoG 2023 Semi-Supervised Learning for High-Fidelity Fluid Flow Reconstruction Cong Fu, Jacob Helwig, Shuiwang Ji

NeurIPS 2023 Towards Symmetry-Aware Generation of Periodic Materials Youzhi Luo, Chengkai Liu, Shuiwang Ji

NeurIPS 2023 Video Timeline Modeling for News Story Understanding Meng Liu, Mingda Zhang, Jialu Liu, Hanjun Dai, Ming-Hsuan Yang, Shuiwang Ji, Zheyun Feng, Boqing Gong

ICLR 2022 An Autoregressive Flow Model for 3D Molecular Geometry Generation from Scratch Youzhi Luo, Shuiwang Ji

NeurIPS 2022 ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs Limei Wang, Yi Liu, Yuchao Lin, Haoran Liu, Shuiwang Ji

NeurIPS 2022 GOOD: A Graph Out-of-Distribution Benchmark Shurui Gui, Xiner Li, Limei Wang, Shuiwang Ji

ICML 2022 Generating 3D Molecules for Target Protein Binding Meng Liu, Youzhi Luo, Kanji Uchino, Koji Maruhashi, Shuiwang Ji

ICML 2022 GraphFM: Improving Large-Scale GNN Training via Feature Momentum Haiyang Yu, Limei Wang, Bokun Wang, Meng Liu, Tianbao Yang, Shuiwang Ji

NeurIPS 2022 Periodic Graph Transformers for Crystal Material Property Prediction Keqiang Yan, Yi Liu, Yuchao Lin, Shuiwang Ji

ICML 2022 Self-Supervised Representation Learning via Latent Graph Prediction Yaochen Xie, Zhao Xu, Shuiwang Ji

ICLR 2022 Spherical Message Passing for 3D Molecular Graphs Yi Liu, Limei Wang, Meng Liu, Yuchao Lin, Xuan Zhang, Bora Oztekin, Shuiwang Ji

NeurIPS 2022 Task-Agnostic Graph Explanations Yaochen Xie, Sumeet Katariya, Xianfeng Tang, Edward Huang, Nikhil Rao, Karthik Subbian, Shuiwang Ji

NeurIPS 2021 ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs Zhanqiu Zhang, Jie Wang, Jiajun Chen, Shuiwang Ji, Feng Wu

MLOSS 2021 DIG: A Turnkey Library for Diving into Graph Deep Learning Research Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan, Shurui Gui, Haiyang Yu, Zhao Xu, Jingtun Zhang, Yi Liu, Keqiang Yan, Haoran Liu, Cong Fu, Bora M Oztekin, Xuan Zhang, Shuiwang Ji

NeurIPSW 2021 Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks Meng Liu, Cong Fu, Xuan Zhang, Limei Wang, Yaochen Xie, Hao Yuan, Youzhi Luo, Zhao Xu, Shenglong Xu, Shuiwang Ji

ICML 2021 GraphDF: A Discrete Flow Model for Molecular Graph Generation Youzhi Luo, Keqiang Yan, Shuiwang Ji

ICLRW 2021 GraphEBM: Molecular Graph Generation with Energy-Based Models Meng Liu, Keqiang Yan, Bora Oztekin, Shuiwang Ji

ICML 2021 On Explainability of Graph Neural Networks via Subgraph Explorations Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji

NeurIPS 2021 Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence Qi Qi, Youzhi Luo, Zhao Xu, Shuiwang Ji, Tianbao Yang

AAAI 2020 A Multi-Scale Approach for Graph Link Prediction Lei Cai, Shuiwang Ji

AAAI 2020 Adaptive Convolutional ReLUs Hongyang Gao, Lei Cai, Shuiwang Ji

ICLR 2020 Kronecker Attention Networks Hongyang Gao, Zhengyang Wang, Shuiwang Ji

NeurIPS 2020 Noise2Same: Optimizing a Self-Supervised Bound for Image Denoising Yaochen Xie, Zhengyang Wang, Shuiwang Ji

AAAI 2020 Non-Local U-Nets for Biomedical Image Segmentation Zhengyang Wang, Na Zou, Dinggang Shen, Shuiwang Ji

ICLR 2020 StructPool: Structured Graph Pooling via Conditional Random Fields Hao Yuan, Shuiwang Ji

IJCAI 2019 Dense Transformer Networks for Brain Electron Microscopy Image Segmentation Jun Li, Yongjun Chen, Lei Cai, Ian Davidson, Shuiwang Ji

ICML 2019 Graph U-Nets Hongyang Gao, Shuiwang Ji

AAAI 2019 Interpreting Deep Models for Text Analysis via Optimization and Regularization Methods Hao Yuan, Yongjun Chen, Xia Hu, Shuiwang Ji

NeurIPS 2018 ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions Hongyang Gao, Zhengyang Wang, Shuiwang Ji

ICML 2010 3D Convolutional Neural Networks for Human Action Recognition Shuiwang Ji, Wei Xu, Ming Yang, Kai Yu

ICML 2009 A Least Squares Formulation for a Class of Generalized Eigenvalue Problems in Machine Learning Liang Sun, Shuiwang Ji, Jieping Ye

ICML 2009 An Accelerated Gradient Method for Trace Norm Minimization Shuiwang Ji, Jieping Ye

IJCAI 2009 DrosophilaGene Expression Pattern Annotation Through Multi-Instance Multi-Label Learning Ying-Xin Li, Shuiwang Ji, Sudhir Kumar, Jieping Ye, Zhi-Hua Zhou

IJCAI 2009 Linear Dimensionality Reduction for Multi-Label Classification Shuiwang Ji, Jieping Ye

UAI 2009 Multi-Task Feature Learning via Efficient L2, 1-Norm Minimization Jun Liu, Shuiwang Ji, Jieping Ye

IJCAI 2009 On the Equivalence Between Canonical Correlation Analysis and Orthonormalized Partial Least Squares Liang Sun, Shuiwang Ji, Shipeng Yu, Jieping Ye

ICML 2008 A Least Squares Formulation for Canonical Correlation Analysis Liang Sun, Shuiwang Ji, Jieping Ye

CVPR 2008 A Unified Framework for Generalized Linear Discriminant Analysis Shuiwang Ji, Jieping Ye

JMLR 2008 Multi-Class Discriminant Kernel Learning via Convex Programming Jieping Ye, Shuiwang Ji, Jianhui Chen

NeurIPS 2008 Multi-Label Multiple Kernel Learning Shuiwang Ji, Liang Sun, Rong Jin, Jieping Ye

ICML 2007 Discriminant Kernel and Regularization Parameter Learning via Semidefinite Programming Jieping Ye, Jianhui Chen, Shuiwang Ji