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ORCIDShuiwang Ji
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- affiliation: Texas A&M University, College Station, TX, USA
- affiliation (former): Old Dominion University, Norfolk, USA
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2020 – today
- 2024
[j66]Shurui Gui
, Hao Yuan, Jie Wang, Qicheng Lao, Kang Li, Shuiwang Ji:
FlowX: Towards Explainable Graph Neural Networks via Message Flows. IEEE Trans. Pattern Anal. Mach. Intell. 46(7): 4567-4578 (2024)- [j65]Meng Liu, Haiyang Yu, Shuiwang Ji:
Empowering GNNs via Edge-Aware Weisfeiler-Leman Algorithm. Trans. Mach. Learn. Res. 2024 (2024) - [j64]Yaochen Xie, Ziqian Xie, Sheikh Muhammad Saiful Islam, Degui Zhi, Shuiwang Ji:
Genetic InfoMax: Exploring Mutual Information Maximization in High-Dimensional Imaging Genetics Studies. Trans. Mach. Learn. Res. 2024 (2024) - [c112]Yu Zhang, Xiusi Chen, Bowen Jin, Sheng Wang, Shuiwang Ji, Wei Wang, Jiawei Han:
A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery. EMNLP 2024: 8783-8817 - [c111]Montgomery Bohde, Meng Liu, Alexandra Saxton, Shuiwang Ji:
On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods. ICLR 2024 - [c110]Shurui Gui, Xiner Li, Shuiwang Ji:
Active Test-Time Adaptation: Theoretical Analyses and An Algorithm. ICLR 2024 - [c109]Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
Complete and Efficient Graph Transformers for Crystal Material Property Prediction. ICLR 2024 - [c108]Xuan Zhang, Jacob Helwig, Yuchao Lin, Yaochen Xie, Cong Fu, Stephan Wojtowytsch, Shuiwang Ji:
SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations. ICLR 2024 - [c107]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 C. 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 Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao:
Position: TrustLLM: Trustworthiness in Large Language Models. ICML 2024 - [c106]Xiner Li, Shurui Gui, Youzhi Luo, Shuiwang Ji:
Graph Structure Extrapolation for Out-of-Distribution Generalization. ICML 2024 - [c105]Yuchao Lin, Jacob Helwig, Shurui Gui, Shuiwang Ji:
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency. ICML 2024 - [c104]Keqiang Yan, Alexandra Saxton, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction. ICML 2024 - [c103]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. SDM 2024: 343-351 - [c102]Cong Fu, Xuan Zhang, Huixin Zhang, Hongyi Ling, Shenglong Xu, Shuiwang Ji:
Lattice Convolutional Networks for Learning Ground States of Quantum Many-Body Systems. SDM 2024: 490-498 - [i98]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 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, John C. 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 Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao:
TrustLLM: Trustworthiness in Large Language Models. CoRR abs/2401.05561 (2024) - [i97]Montgomery Bohde, Meng Liu, Alexandra Saxton, Shuiwang Ji:
On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods. CoRR abs/2403.04929 (2024) - [i96]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) - [i95]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 (2024) - [i94]Shurui Gui, Xiner Li, Shuiwang Ji:
Active Test-Time Adaptation: Theoretical Analyses and An Algorithm. CoRR abs/2404.05094 (2024) - [i93]Yuchao Lin, Jacob Helwig, Shurui Gui, Shuiwang Ji:
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency. CoRR abs/2406.07598 (2024) - [i92]Yu Zhang, Xiusi Chen, Bowen Jin, Sheng Wang, Shuiwang Ji, Wei Wang, Jiawei Han:
A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery. CoRR abs/2406.10833 (2024) - [i91]Keqiang Yan, Alexandra Saxton, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction. CoRR abs/2406.12888 (2024) - [i90]Ziqi Wang, Hanlin Zhang, Xiner Li, Kuan-Hao Huang, Chi Han, Shuiwang Ji, Sham M. Kakade, Hao Peng, Heng Ji:
Eliminating Position Bias of Language Models: A Mechanistic Approach. CoRR abs/2407.01100 (2024) - [i89]Xiner Li, Limei Wang, Youzhi Luo, Carl Edwards, Shurui Gui, Yuchao Lin, Heng Ji, Shuiwang Ji:
Geometry Informed Tokenization of Molecules for Language Model Generation. CoRR abs/2408.10120 (2024) - [i88]Sambhav Khurana, Xiner Li, Shurui Gui, Shuiwang Ji:
A Hierarchical Language Model For Interpretable Graph Reasoning. CoRR abs/2410.22372 (2024) - 2023
- [j63]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) - [j62]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): 1652-1667 (2023) - [j61]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) - [j60]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) - [j59]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) - [j58]Zhengyang Wang, Shuiwang Ji:
Second-Order Pooling for Graph Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 45(6): 6870-6880 (2023) - [j57]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 Networks Learn. Syst. 34(5): 2528-2538 (2023) - [c101]Hongyi Ling, Zhimeng Jiang, Youzhi Luo, Shuiwang Ji, Na Zou:
Learning Fair Graph Representations via Automated Data Augmentations. ICLR 2023 - [c100]Meng Liu, Haoran Liu, Shuiwang Ji:
Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models. ICLR 2023 - [c99]Youzhi Luo, Michael McThrow, Wing Yee Au, Tao Komikado, Kanji Uchino, Koji Maruhashi, Shuiwang Ji:
Automated Data Augmentations for Graph Classification. ICLR 2023 - [c98]Limei Wang, Haoran Liu, Yi Liu, Jerry Kurtin, Shuiwang Ji:
Learning Hierarchical Protein Representations via Complete 3D Graph Networks. ICLR 2023 - [c97]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 - [c96]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 - [c95]Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji, Na Zou:
Graph Mixup with Soft Alignments. ICML 2023: 21335-21349 - [c94]Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian. ICML 2023: 40412-40424 - [c93]Minkai Xu, Meng Liu, Wengong Jin, Shuiwang Ji, Jure Leskovec, Stefano Ermon:
Graph and Geometry Generative Modeling for Drug Discovery. KDD 2023: 5833-5834 - [c92]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. LoG 2023: 29 - [c91]Cong Fu, Jacob Helwig, Shuiwang Ji:
Semi-Supervised Learning for High-Fidelity Fluid Flow Reconstruction. LoG 2023: 36 - [c90]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. NeurIPS 2023 - [c89]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 - [c88]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 - [c87]Youzhi Luo, Chengkai Liu, Shuiwang Ji:
Towards Symmetry-Aware Generation of Periodic Materials. NeurIPS 2023 - [c86]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 - [i87]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. CoRR abs/2302.09601 (2023) - [i86]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) - [i85]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 abs/2304.04757 (2023) - [i84]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 abs/2305.04120 (2023) - [i83]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) - [i82]Xuan Zhang, Shenglong Xu, Shuiwang Ji:
A Score-Based Model for Learning Neural Wavefunctions. CoRR abs/2305.16540 (2023) - [i81]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) - [i80]Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian. CoRR abs/2306.04922 (2023) - [i79]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) - [i78]Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji, Na Zou:
Graph Mixup with Soft Alignments. CoRR abs/2306.06788 (2023) - [i77]Xiner Li, Shurui Gui, Youzhi Luo, Shuiwang Ji:
Graph Structure and Feature Extrapolation for Out-of-Distribution Generalization. CoRR abs/2306.08076 (2023) - [i76]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) - [i75]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) - [i74]Youzhi Luo, Chengkai Liu, Shuiwang Ji:
Towards Symmetry-Aware Generation of Periodic Materials. CoRR abs/2307.02707 (2023) - [i73]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 Xie, Xiang Fu, Alex Strasser, 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:
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR abs/2307.08423 (2023) - [i72]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) - [i71]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 abs/2309.15132 (2023) - 2022
- [j56]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) - [j55]Hongyang Gao, Shuiwang Ji:
Graph U-Nets. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 4948-4960 (2022) - [j54]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) - [j53]Meng Liu, Zhengyang Wang, Shuiwang Ji:
Non-Local Graph Neural Networks. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 10270-10276 (2022) - [j52]Yaochen Xie, Yu Ding, Shuiwang Ji:
Augmented Equivariant Attention Networks for Microscopy Image Transformation. IEEE Trans. Medical Imaging 41(11): 3194-3206 (2022) - [c85]Yi Liu, Limei Wang, Meng Liu, Yuchao Lin, Xuan Zhang, Bora Oztekin, Shuiwang Ji:
Spherical Message Passing for 3D Molecular Graphs. ICLR 2022 - [c84]Youzhi Luo, Shuiwang Ji:
An Autoregressive Flow Model for 3D Molecular Geometry Generation from Scratch. ICLR 2022 - [c83]Meng Liu, Youzhi Luo, Kanji Uchino, Koji Maruhashi, Shuiwang Ji:
Generating 3D Molecules for Target Protein Binding. ICML 2022: 13912-13924 - [c82]Yaochen Xie, Zhao Xu, Shuiwang Ji:
Self-Supervised Representation Learning via Latent Graph Prediction. ICML 2022: 24460-24477 - [c81]Haiyang Yu, Limei Wang, Bokun Wang, Meng Liu, Tianbao Yang, Shuiwang Ji:
GraphFM: Improving Large-Scale GNN Training via Feature Momentum. ICML 2022: 25684-25701 - [c80]Rui Yang, Jie Wang, Zijie Geng, Mingxuan Ye, Shuiwang Ji, Bin Li, Feng Wu:
Learning Task-relevant Representations for Generalization via Characteristic Functions of Reward Sequence Distributions. KDD 2022: 2242-2252 - [c79]Shuiwang Ji, Meng Liu, Yi Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Zhao Xu, Haiyang Yu:
Frontiers of Graph Neural Networks with DIG. KDD 2022: 4796-4797 - [c78]Shurui Gui, Xiner Li, Limei Wang, Shuiwang Ji:
GOOD: A Graph Out-of-Distribution Benchmark. NeurIPS 2022 - [c77]Limei Wang, Yi Liu, Yuchao Lin, Haoran Liu, Shuiwang Ji:
ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs. NeurIPS 2022 - [c76]Yaochen Xie, Sumeet Katariya, Xianfeng Tang, Edward W. Huang, Nikhil Rao, Karthik Subbian, Shuiwang Ji:
Task-Agnostic Graph Explanations. NeurIPS 2022 - [c75]Keqiang Yan, Yi Liu, Yuchao Lin, Shuiwang Ji:
Periodic Graph Transformers for Crystal Material Property Prediction. NeurIPS 2022 - [c74]Meng Liu, Shuiwang Ji:
Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences. SDM 2022: 55-63 - [i70]Meng Liu, Shuiwang Ji:
Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences. CoRR abs/2202.03341 (2022) - [i69]Yaochen Xie, Zhao Xu, Shuiwang Ji:
Self-Supervised Representation Learning via Latent Graph Prediction. CoRR abs/2202.08333 (2022) - [i68]Yaochen Xie, Sumeet Katariya, Xianfeng Tang, Edward W. Huang, Nikhil Rao, Karthik Subbian, Shuiwang Ji:
Task-Agnostic Graph Explanations. CoRR abs/2202.08335 (2022) - [i67]Youzhi Luo, Michael McThrow, Wing Yee Au, Tao Komikado, Kanji Uchino, Koji Maruhashi, Shuiwang Ji:
Automated Data Augmentations for Graph Classification. CoRR abs/2202.13248 (2022) - [i66]Jie Wang, Zhanqiu Zhang, Zhihao Shi, Jianyu Cai, Shuiwang Ji, Feng Wu:
Duality-Induced Regularizer for Semantic Matching Knowledge Graph Embeddings. CoRR abs/2203.12949 (2022) - [i65]Meng Liu, Youzhi Luo, Kanji Uchino, Koji Maruhashi, Shuiwang Ji:
Generating 3D Molecules for Target Protein Binding. CoRR abs/2204.09410 (2022) - [i64]Rui Yang, Jie Wang, Zijie Geng, Mingxuan Ye, Shuiwang Ji, Bin Li, Feng Wu:
Learning Task-relevant Representations for Generalization via Characteristic Functions of Reward Sequence Distributions. CoRR abs/2205.10218 (2022) - [i63]Meng Liu, Haiyang Yu, Shuiwang Ji:
Your Neighbors Are Communicating: Towards Powerful and Scalable Graph Neural Networks. CoRR abs/2206.02059 (2022) - [i62]Haiyang Yu, Limei Wang, Bokun Wang, Meng Liu, Tianbao Yang, Shuiwang Ji:
GraphFM: Improving Large-Scale GNN Training via Feature Momentum. CoRR abs/2206.07161 (2022) - [i61]Cong Fu, Xuan Zhang, Huixin Zhang, Hongyi Ling, Shenglong Xu, Shuiwang Ji:
Lattice Convolutional Networks for Learning Ground States of Quantum Many-Body Systems. CoRR abs/2206.07370 (2022) - [i60]Xueliang Wang, Jianyu Cai, Shuiwang Ji, Houqiang Li, Feng Wu, Jie Wang:
Self-Adaptive Label Augmentation for Semi-supervised Few-shot Classification. CoRR abs/2206.08150 (2022) - [i59]Shurui Gui, Xiner Li, Limei Wang, Shuiwang Ji:
GOOD: A Graph Out-of-Distribution Benchmark. CoRR abs/2206.08452 (2022) - [i58]Limei Wang, Yi Liu, Yuchao Lin, Haoran Liu, Shuiwang Ji:
ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs. CoRR abs/2206.08515 (2022) - [i57]Shurui Gui, Hao Yuan, Jie Wang, Qicheng Lao, Kang Li, Shuiwang Ji:
FlowX: Towards Explainable Graph Neural Networks via Message Flows. CoRR abs/2206.12987 (2022) - [i56]Limei Wang, Haoran Liu, Yi Liu, Jerry Kurtin, Shuiwang Ji:
Learning Protein Representations via Complete 3D Graph Networks. CoRR abs/2207.12600 (2022) - [i55]Keqiang Yan, Yi Liu, Yuchao Lin, Shuiwang Ji:
Periodic Graph Transformers for Crystal Material Property Prediction. CoRR abs/2209.11807 (2022) - [i54]Meng Liu, Haoran Liu, Shuiwang Ji:
Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models. CoRR abs/2210.05782 (2022) - [i53]Haitao Lin, Yufei Huang, Meng Liu, Xuanjing Li, Shuiwang Ji, Stan Z. Li:
DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding. CoRR abs/2211.11214 (2022) - 2021
- [j51]Zhengyang Wang, Shuiwang Ji:
Smoothed dilated convolutions for improved dense prediction. Data Min. Knowl. Discov. 35(4): 1470-1496 (2021) - [j50]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 Oztekin, Xuan Zhang, Shuiwang Ji:
DIG: A Turnkey Library for Diving into Graph Deep Learning Research. J. Mach. Learn. Res. 22: 240:1-240:9 (2021) - [j49]Zhengyang Wang, Yaochen Xie, Shuiwang Ji:
Global voxel transformer networks for augmented microscopy. Nat. Mach. Intell. 3(2): 161-171 (2021) - [j48]Hongyang Gao, Zhengyang Wang, Lei Cai, Shuiwang Ji:
ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions. IEEE Trans. Pattern Anal. Mach. Intell. 43(8): 2570-2581 (2021) - [j47]Hongyang Gao, Yi Liu, Shuiwang Ji:
Topology-Aware Graph Pooling Networks. IEEE Trans. Pattern Anal. Mach. Intell. 43(12): 4512-4518 (2021) - [j46]Yi Liu, Shuiwang Ji:
CleftNet: Augmented Deep Learning for Synaptic Cleft Detection From Brain Electron Microscopy. IEEE Trans. Medical Imaging 40(12): 3507-3518 (2021) - [c73]Yuan Luo, Fei Wang, Marinka Zitnik, Shuiwang Ji:
Graph Based Machine Learning for Healthcare: State of the Art, Challenges, and Opportunities. AMIA 2021 - [c72]Yushun Dong, Kaize Ding, Brian Jalaian, Shuiwang Ji, Jundong Li:
AdaGNN: Graph Neural Networks with Adaptive Frequency Response Filter. CIKM 2021: 392-401 - [c71]Youzhi Luo, Keqiang Yan, Shuiwang Ji:
GraphDF: A Discrete Flow Model for Molecular Graph Generation. ICML 2021: 7192-7203 - [c70]Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji:
On Explainability of Graph Neural Networks via Subgraph Explorations.