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Generating 3D Molecules for Target Protein Binding.
Meng Liu, Youzhi Luo, Kanji Uchino, Koji Maruhashi, Shuiwang Ji: Generating 3D Molecules for Target Protein Binding. ICML 2022: 13912-13924
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An Autoregressive Flow Model for 3D Molecular Geometry Generation from Scratch.
Youzhi Luo, Shuiwang Ji: An Autoregressive Flow Model for 3D Molecular Geometry Generation from Scratch. ICLR 2022
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Spherical Message Passing for 3D Molecular Graphs.
Yi Liu, Limei Wang, Meng Liu, Yuchao Lin, Xuan Zhang, Bora Oztekin, Shuiwang Ji: Spherical Message Passing for 3D Molecular Graphs. ICLR 2022
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Augmented Equivariant Attention Networks for Microscopy Image Transformation.
Yaochen Xie, Yu Ding, Shuiwang Ji: Augmented Equivariant Attention Networks for Microscopy Image Transformation. IEEE Trans. Medical Imaging 41(11): 3194-3206 (2022)
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Non-Local Graph Neural Networks.
Meng Liu, Zhengyang Wang, Shuiwang Ji: Non-Local Graph Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 10270-10276 (2022)
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Line Graph Neural Networks for Link Prediction.
Lei Cai, Jundong Li, Jie Wang, Shuiwang Ji: Line Graph Neural Networks for Link Prediction. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 5103-5113 (2022)
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Graph U-Nets.
Hongyang Gao, Shuiwang Ji: Graph U-Nets. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 4948-4960 (2022)
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Interpreting Image Classifiers by Generating Discrete Masks.
Hao Yuan, Lei Cai, Xia Hu, Jie Wang, Shuiwang Ji: Interpreting Image Classifiers by Generating Discrete Masks. IEEE Trans. Pattern Anal. Mach. Intell. 44(4): 2019-2030 (2022)
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Genetic InfoMax: Exploring Mutual Information Maximization in...
Yaochen Xie, Ziqian Xie, Sheikh Muhammad Saiful Islam, Degui Zhi, Shuiwang Ji: Genetic InfoMax: Exploring Mutual Information Maximization in High-Dimensional Imaging Genetics Studies. CoRR...
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Video Timeline Modeling For News Story Understanding.
Meng Liu, Mingda Zhang, Jialu Liu, Hanjun Dai, Ming-Hsuan Yang, Shuiwang Ji, Zheyun Feng, Boqing Gong: Video Timeline Modeling For News Story Understanding. CoRR abs/2309.13446 (2023)
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Artificial Intelligence for Science in Quantum, Atomistic, and Continuum...
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, Haiyang Yu, Yuqing...
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Towards Symmetry-Aware Generation of Periodic Materials.
Youzhi Luo, Chengkai Liu, Shuiwang Ji: Towards Symmetry-Aware Generation of Periodic Materials. CoRR abs/2307.02707 (2023)
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Efficient Approximations of Complete Interatomic Potentials for Crystal...
Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian, Shuiwang Ji: Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction. CoRR abs/2306.10045 (2023)
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QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules.
Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji: QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules. CoRR abs/2306.09549 (2023)
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Graph Structure and Feature Extrapolation for Out-of-Distribution...
Xiner Li, Shurui Gui, Youzhi Luo, Shuiwang Ji: Graph Structure and Feature Extrapolation for Out-of-Distribution Generalization. CoRR abs/2306.08076 (2023)
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Graph Mixup with Soft Alignments.
Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji, Na Zou: Graph Mixup with Soft Alignments. CoRR abs/2306.06788 (2023)
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Group Equivariant Fourier Neural Operators for Partial Differential Equations.
Jacob Helwig, Xuan Zhang, Cong Fu, Jerry Kurtin, Stephan Wojtowytsch, Shuiwang Ji: Group Equivariant Fourier Neural Operators for Partial Differential Equations. CoRR abs/2306.05697 (2023)
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Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian.
Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji: Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian. CoRR abs/2306.04922 (2023)
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Joint Learning of Label and Environment Causal Independence for Graph...
Shurui Gui, Meng Liu, Xiner Li, Youzhi Luo, Shuiwang Ji: Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization. CoRR abs/2306.01103 (2023)
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A Score-Based Model for Learning Neural Wavefunctions.
Xuan Zhang, Shenglong Xu, Shuiwang Ji: A Score-Based Model for Learning Neural Wavefunctions. CoRR abs/2305.16540 (2023)
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3D Molecular Geometry Analysis with 2D Graphs.
Zhao Xu, Yaochen Xie, Youzhi Luo, Xuan Zhang, Xinyi Xu, Meng Liu, Kaleb Dickerson, Cheng Deng, Maho Nakata, Shuiwang Ji: 3D Molecular Geometry Analysis with 2D Graphs. CoRR abs/2305.13315 (2023)
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A Latent Diffusion Model for Protein Structure Generation.
Cong Fu, Keqiang Yan, Limei Wang, Wing Yee Au, Michael McThrow, Tao Komikado, Koji Maruhashi, Kanji Uchino, Xiaoning Qian, Shuiwang Ji: A Latent Diffusion Model for Protein Structure Generation. CoRR...
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A new perspective on building efficient and expressive 3D equivariant graph...
Weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, Carla Gomes, Zhi-Ming Ma: A new perspective on building efficient and expressive 3D equivariant graph neural networks. CoRR...
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Provably Convergent Subgraph-wise Sampling for Fast GNN Training.
Jie Wang, Zhihao Shi, Xize Liang, Shuiwang Ji, Bin Li, Feng Wu: Provably Convergent Subgraph-wise Sampling for Fast GNN Training. CoRR abs/2303.11081 (2023)
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Generalization in Visual Reinforcement Learning with the Reward Sequence...
Jie Wang, Rui Yang, Zijie Geng, Zhihao Shi, Mingxuan Ye, Qi Zhou, Shuiwang Ji, Bin Li, Yongdong Zhang, Feng Wu: Generalization in Visual Reinforcement Learning with the Reward Sequence Distribution....
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QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules.
Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji: QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules. NeurIPS 2023
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Towards Symmetry-Aware Generation of Periodic Materials.
Youzhi Luo, Chengkai Liu, Shuiwang Ji: Towards Symmetry-Aware Generation of Periodic Materials. NeurIPS 2023
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Video Timeline Modeling For News Story Understanding.
Meng Liu, Mingda Zhang, Jialu Liu, Hanjun Dai, Ming-Hsuan Yang, Shuiwang Ji, Zheyun Feng, Boqing Gong: Video Timeline Modeling For News Story Understanding. NeurIPS 2023
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Joint Learning of Label and Environment Causal Independence for Graph...
Shurui Gui, Meng Liu, Xiner Li, Youzhi Luo, Shuiwang Ji: Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization. NeurIPS 2023
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A new perspective on building efficient and expressive 3D equivariant graph...
Weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, Carla P. Gomes, Zhi-Ming Ma: A new perspective on building efficient and expressive 3D equivariant graph neural networks....
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Graph and Geometry Generative Modeling for Drug Discovery.
Minkai Xu, Meng Liu, Wengong Jin, Shuiwang Ji, Jure Leskovec, Stefano Ermon: Graph and Geometry Generative Modeling for Drug Discovery. KDD 2023: 5833-5834
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Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian.
Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji: Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian. ICML 2023: 40412-40424
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Graph Mixup with Soft Alignments.
Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji, Na Zou: Graph Mixup with Soft Alignments. ICML 2023: 21335-21349
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Efficient Approximations of Complete Interatomic Potentials for Crystal...
Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian, Shuiwang Ji: Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction. ICML 2023: 21260-21287
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Group Equivariant Fourier Neural Operators for Partial Differential Equations.
Jacob Helwig, Xuan Zhang, Cong Fu, Jerry Kurtin, Stephan Wojtowytsch, Shuiwang Ji: Group Equivariant Fourier Neural Operators for Partial Differential Equations. ICML 2023: 12907-12930
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Learning Hierarchical Protein Representations via Complete 3D Graph Networks.
Limei Wang, Haoran Liu, Yi Liu, Jerry Kurtin, Shuiwang Ji: Learning Hierarchical Protein Representations via Complete 3D Graph Networks. ICLR 2023
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Automated Data Augmentations for Graph Classification.
Youzhi Luo, Michael McThrow, Wing Yee Au, Tao Komikado, Kanji Uchino, Koji Maruhashi, Shuiwang Ji: Automated Data Augmentations for Graph Classification. ICLR 2023
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Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models.
Meng Liu, Haoran Liu, Shuiwang Ji: Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models. ICLR 2023
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Learning Fair Graph Representations via Automated Data Augmentations.
Hongyi Ling, Zhimeng Jiang, Youzhi Luo, Shuiwang Ji, Na Zou: Learning Fair Graph Representations via Automated Data Augmentations. ICLR 2023
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Deep Low-Shot Learning for Biological Image Classification and Visualization...
Lei Cai, Zhengyang Wang, Rob Kulathinal, Sudhir Kumar, Shuiwang Ji: Deep Low-Shot Learning for Biological Image Classification and Visualization From Limited Training Samples. IEEE Trans. Neural...
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Second-Order Pooling for Graph Neural Networks.
Zhengyang Wang, Shuiwang Ji: Second-Order Pooling for Graph Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 45(6): 6870-6880 (2023)
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Explainability in Graph Neural Networks: A Taxonomic Survey.
Hao Yuan, Haiyang Yu, Shurui Gui, Shuiwang Ji: Explainability in Graph Neural Networks: A Taxonomic Survey. IEEE Trans. Pattern Anal. Mach. Intell. 45(5): 5782-5799 (2023)
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Group Contrastive Self-Supervised Learning on Graphs.
Xinyi Xu, Cheng Deng, Yaochen Xie, Shuiwang Ji: Group Contrastive Self-Supervised Learning on Graphs. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 3169-3180 (2023)
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Self-Supervised Learning of Graph Neural Networks: A Unified Review.
Yaochen Xie, Zhao Xu, Jingtun Zhang, Zhengyang Wang, Shuiwang Ji: Self-Supervised Learning of Graph Neural Networks: A Unified Review. IEEE Trans. Pattern Anal. Mach. Intell. 45(2): 2412-2429 (2023)
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Duality-Induced Regularizer for Semantic Matching Knowledge Graph Embeddings.
Jie Wang, Zhanqiu Zhang, Zhihao Shi, Jianyu Cai, Shuiwang Ji, Feng Wu: Duality-Induced Regularizer for Semantic Matching Knowledge Graph Embeddings. IEEE Trans. Pattern Anal. Mach. Intell. 45(2):...
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Towards Improved and Interpretable Deep Metric Learning via Attentive Grouping.
Xinyi Xu, Zhengyang Wang, Cheng Deng, Hao Yuan, Shuiwang Ji: Towards Improved and Interpretable Deep Metric Learning via Attentive Grouping. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 1189-1200 (2023)
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TrustLLM: Trustworthiness in Large Language Models.
Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming...
View ArticleComplete and Efficient Graph Transformers for Crystal Material Property...
Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji: Complete and Efficient Graph Transformers for Crystal Material Property Prediction. CoRR abs/2403.11857 (2024)
View ArticleOn the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods.
Montgomery Bohde, Meng Liu, Alexandra Saxton, Shuiwang Ji: On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods. CoRR abs/2403.04929 (2024)
View ArticleSineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential...
Xuan Zhang, Jacob Helwig, Yuchao Lin, Yaochen Xie, Cong Fu, Stephan Wojtowytsch, Shuiwang Ji: SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations. CoRR abs/2403.19507...
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