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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. ICML 2021: 12241-12252 - [c69]Sina Mohseni, Fan Yang, Shiva K. Pentyala, Mengnan Du, Yi Liu, Nic Lupfer, Xia Hu, Shuiwang Ji, Eric D. Ragan:
Machine Learning Explanations to Prevent Overtrust in Fake News Detection. ICWSM 2021: 421-431 - [c68]Qi Qi, Youzhi Luo, Zhao Xu, Shuiwang Ji, Tianbao Yang:
Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence. NeurIPS 2021: 1752-1765 - [c67]Zhanqiu Zhang, Jie Wang, Jiajun Chen, Shuiwang Ji, Feng Wu:
ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs. NeurIPS 2021: 19172-19183 - [i52]Hao Yuan, Shuiwang Ji:
Node2Seq: Towards Trainable Convolutions in Graph Neural Networks. CoRR abs/2101.01849 (2021) - [i51]Yi Liu, Shuiwang Ji:
CleftNet: Augmented Deep Learning for Synaptic Cleft Detection from Brain Electron Microscopy. CoRR abs/2101.04266 (2021) - [i50]Yi Liu, Shuiwang Ji:
A Multi-Stage Attentive Transfer Learning Framework for Improving COVID-19 Diagnosis. CoRR abs/2101.05410 (2021) - [i49]Meng Liu, Keqiang Yan, Bora Oztekin, Shuiwang Ji:
GraphEBM: Molecular Graph Generation with Energy-Based Models. CoRR abs/2102.00546 (2021) - [i48]Youzhi Luo, Keqiang Yan, Shuiwang Ji:
GraphDF: A Discrete Flow Model for Molecular Graph Generation. CoRR abs/2102.01189 (2021) - [i47]Yi Liu, Limei Wang, Meng Liu, Xuan Zhang, Bora Oztekin, Shuiwang Ji:
Spherical Message Passing for 3D Graph Networks. CoRR abs/2102.05013 (2021) - [i46]Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji:
On Explainability of Graph Neural Networks via Subgraph Explorations. CoRR abs/2102.05152 (2021) - [i45]Yaochen Xie, Zhao Xu, Zhengyang Wang, Shuiwang Ji:
Self-Supervised Learning of Graph Neural Networks: A Unified Review. CoRR abs/2102.10757 (2021) - [i44]Shuai Zheng, Zhenfeng Zhu, Zhizhe Liu, Shuiwang Ji, Yao Zhao:
Adversarial Graph Disentanglement. CoRR abs/2103.07295 (2021) - [i43]Hongyang Gao, Yi Liu, Xuan Zhang, Shuiwang Ji:
Sent2Matrix: Folding Character Sequences in Serpentine Manifolds for Two-Dimensional Sentence. CoRR abs/2103.08387 (2021) - [i42]Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan, Shurui Gui, Zhao Xu, Haiyang Yu, Jingtun Zhang, Yi Liu, Keqiang Yan, Bora Oztekin, Haoran Liu, Xuan Zhang, Cong Fu, Shuiwang Ji:
DIG: A Turnkey Library for Diving into Graph Deep Learning Research. CoRR abs/2103.12608 (2021) - [i41]Qi Qi, Youzhi Luo, Zhao Xu, Shuiwang Ji, Tianbao Yang:
Stochastic Optimization of Area Under Precision-Recall Curve for Deep Learning with Provable Convergence. CoRR abs/2104.08736 (2021) - [i40]Yushun Dong, Kaize Ding, Brian Jalaian, Shuiwang Ji, Jundong Li:
Graph Neural Networks with Adaptive Frequency Response Filter. CoRR abs/2104.12840 (2021) - [i39]Meng Liu, Cong Fu, Xuan Zhang, Limei Wang, Yaochen Xie, Hao Yuan, Youzhi Luo, Zhao Xu, Shenglong Xu, Shuiwang Ji:
Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks. CoRR abs/2106.08551 (2021) - [i38]Xinyi Xu, Cheng Deng, Yaochen Xie, Shuiwang Ji:
Group Contrastive Self-Supervised Learning on Graphs. CoRR abs/2107.09787 (2021) - [i37]Zhao Xu, Youzhi Luo, Xuan Zhang, Xinyi Xu, Yaochen Xie, Meng Liu, Kaleb Dickerson, Cheng Deng, Maho Nakata, Shuiwang Ji:
Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs. CoRR abs/2110.01717 (2021) - [i36]Zhanqiu Zhang, Jie Wang, Jiajun Chen, Shuiwang Ji, Feng Wu:
ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs. CoRR abs/2110.13715 (2021) - 2020
- [j45]Hongyang Gao, Hao Yuan, Zhengyang Wang, Shuiwang Ji:
Pixel Transposed Convolutional Networks. IEEE Trans. Pattern Anal. Mach. Intell. 42(5): 1218-1227 (2020) - [j44]Wei Jin, Yaxin Li, Han Xu, Yiqi Wang, Shuiwang Ji, Charu Aggarwal, Jiliang Tang:
Adversarial Attacks and Defenses on Graphs. SIGKDD Explor. 22(2): 19-34 (2020) - [j43]Wenlu Zhang, Rongjian Li, Tao Zeng, Qian Sun, Sudhir Kumar, Jieping Ye, Shuiwang Ji:
Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis. IEEE Trans. Big Data 6(2): 322-333 (2020) - [j42]Yi Liu, Hao Yuan, Zhengyang Wang, Shuiwang Ji:
Global Pixel Transformers for Virtual Staining of Microscopy Images. IEEE Trans. Medical Imaging 39(6): 2256-2266 (2020) - [c66]Lei Cai, Shuiwang Ji:
A Multi-Scale Approach for Graph Link Prediction. AAAI 2020: 3308-3315 - [c65]Hongyang Gao, Lei Cai, Shuiwang Ji:
Adaptive Convolutional ReLUs. AAAI 2020: 3914-3921 - [c64]Zhengyang Wang, Na Zou, Dinggang Shen, Shuiwang Ji:
Non-Local U-Nets for Biomedical Image Segmentation. AAAI 2020: 6315-6322 - [c63]Hanzi Mao, Xi Liu, Nick Duffield, Hao Yuan, Shuiwang Ji, Binayak P. Mohanty:
Context-aware Deep Representation Learning for Geo-spatiotemporal Analysis. ICDM 2020: 392-401 - [c62]Zhengyang Wang, Bunyamin Sisman, Hao Wei, Xin Luna Dong, Shuiwang Ji:
CorDEL: A Contrastive Deep Learning Approach for Entity Linkage. ICDM 2020: 1322-1327 - [c61]Hao Yuan, Shuiwang Ji:
StructPool: Structured Graph Pooling via Conditional Random Fields. ICLR 2020 - [c60]Hongyang Gao, Zhengyang Wang, Shuiwang Ji:
Kronecker Attention Networks. KDD 2020: 229-237 - [c59]Meng Liu, Hongyang Gao, Shuiwang Ji:
Towards Deeper Graph Neural Networks. KDD 2020: 338-348 - [c58]Hao Yuan, Jiliang Tang, Xia Hu, Shuiwang Ji:
XGNN: Towards Model-Level Explanations of Graph Neural Networks. KDD 2020: 430-438 - [c57]Yi Liu, Hao Yuan, Lei Cai, Shuiwang Ji:
Deep Learning of High-Order Interactions for Protein Interface Prediction. KDD 2020: 679-687 - [c56]Yaochen Xie, Zhengyang Wang, Shuiwang Ji:
Noise2Same: Optimizing A Self-Supervised Bound for Image Denoising. NeurIPS 2020 - [c55]Fan Yang, Ninghao Liu, Mengnan Du, Kaixiong Zhou, Shuiwang Ji, Xia Hu:
Deep Neural Networks with Knowledge Instillation. SDM 2020: 370-378 - [d1]Zhengyang Wang, Yaochen Xie, Shuiwang Ji:
zhengyang-wang/GVTNets: Code for "Global Voxel Transformer Networks for Augmented Microscopy". Zenodo, 2020
- [i35]Meng Liu, Zhengyang Wang, Shuiwang Ji:
Non-Local Graph Neural Networks. CoRR abs/2005.14612 (2020) - [i34]Zhengyang Wang, Xia Hu, Shuiwang Ji:
iCapsNets: Towards Interpretable Capsule Networks for Text Classification. CoRR abs/2006.00075 (2020) - [i33]Hao Yuan, Jiliang Tang, Xia Hu, Shuiwang Ji:
XGNN: Towards Model-Level Explanations of Graph Neural Networks. CoRR abs/2006.02587 (2020) - [i32]Hongyang Gao, Zhengyang Wang, Shuiwang Ji:
Kronecker Attention Networks. CoRR abs/2007.08442 (2020) - [i31]Meng Liu, Hongyang Gao, Shuiwang Ji:
Towards Deeper Graph Neural Networks. CoRR abs/2007.09296 (2020) - [i30]Yi Liu, Hao Yuan, Lei Cai, Shuiwang Ji:
Deep Learning of High-Order Interactions for Protein Interface Prediction. CoRR abs/2007.09334 (2020) - [i29]Zhengyang Wang, Shuiwang Ji:
Second-Order Pooling for Graph Neural Networks. CoRR abs/2007.10467 (2020) - [i28]Sina Mohseni, Fan Yang, Shiva K. Pentyala, Mengnan Du, Yi Liu, Nic Lupfer, Xia Hu, Shuiwang Ji, Eric D. Ragan:
Machine Learning Explanations to Prevent Overtrust in Fake News Detection. CoRR abs/2007.12358 (2020) - [i27]Zhengyang Wang, Yaochen Xie, Shuiwang Ji:
Global Voxel Transformer Networks for Augmented Microscopy. CoRR abs/2008.02340 (2020) - [i26]Zhengyang Wang, Bunyamin Sisman, Hao Wei, Xin Luna Dong, Shuiwang Ji:
CorDEL: A Contrastive Deep Learning Approach for Entity Linkage. CoRR abs/2009.07203 (2020) - [i25]Hongyang Gao, Yi Liu, Shuiwang Ji:
Topology-Aware Graph Pooling Networks. CoRR abs/2010.09834 (2020) - [i24]Lei Cai, Jundong Li, Jie Wang, Shuiwang Ji:
Line Graph Neural Networks for Link Prediction. CoRR abs/2010.10046 (2020) - [i23]Lei Cai, Zhengyang Wang, Rob Kulathinal, Sudhir Kumar, Shuiwang Ji:
Deep Low-Shot Learning for Biological Image Classification and Visualization from Limited Training Samples. CoRR abs/2010.10050 (2020) - [i22]Yaochen Xie, Zhengyang Wang, Shuiwang Ji:
Noise2Same: Optimizing A Self-Supervised Bound for Image Denoising. CoRR abs/2010.11971 (2020) - [i21]Yaochen Xie, Yu Ding, Shuiwang Ji:
Augmented Equivariant Attention Networks for Electron Microscopy Image Super-Resolution. CoRR abs/2011.03633 (2020) - [i20]Xinyi Xu, Zhengyang Wang, Cheng Deng, Hao Yuan, Shuiwang Ji:
Towards Improved and Interpretable Deep Metric Learning via Attentive Grouping. CoRR abs/2011.08877 (2020) - [i19]Zhengyang Wang, Meng Liu, Youzhi Luo, Zhao Xu, Yaochen Xie, Limei Wang, Lei Cai, Shuiwang Ji:
MoleculeKit: Machine Learning Methods for Molecular Property Prediction and Drug Discovery. CoRR abs/2012.01981 (2020) - [i18]Hao Yuan, Haiyang Yu, Shurui Gui, Shuiwang Ji:
Explainability in Graph Neural Networks: A Taxonomic Survey. CoRR abs/2012.15445 (2020)
2010 – 2019
- 2019
- [j41]Hao Yuan, Lei Cai, Zhengyang Wang, Xia Hu, Shaoting Zhang, Shuiwang Ji:
Computational modeling of cellular structures using conditional deep generative networks. Bioinform. 35(12): 2141-2149 (2019) - [j40]Debrup Banerjee, Kazi Aminul Islam, Keyi Xue, Gang Mei, Lemin Xiao, Guangfan Zhang, Roger Xu, Cai Lei, Shuiwang Ji, Jiang Li:
A deep transfer learning approach for improved post-traumatic stress disorder diagnosis. Knowl. Inf. Syst. 60(3): 1693-1724 (2019) - [j39]Yujie Feng, Fan Yang, Xichuan Zhou, Yanli Guo, Fang Tang, Fengbo Ren, Jishun Guo, Shuiwang Ji:
A Deep Learning Approach for Targeted Contrast-Enhanced Ultrasound Based Prostate Cancer Detection. IEEE ACM Trans. Comput. Biol. Bioinform. 16(6): 1794-1801 (2019) - [c54]Hao Yuan, Yongjun Chen, Xia Hu, Shuiwang Ji:
Interpreting Deep Models for Text Analysis via Optimization and Regularization Methods. AAAI 2019: 5717-5724 - [c53]Lei Cai, Shuiwang Ji:
An Efficient Policy Gradient Method for Conditional Dialogue Generation. ICDM 2019: 31-40 - [c52]Hao Yuan, Na Zou, Shaoting Zhang, Hanchuan Peng, Shuiwang Ji:
Learning Hierarchical and Shared Features for Improving 3D Neuron Reconstruction. ICDM 2019: 806-815 - [c51]Yi Liu, Hao Yuan, Shuiwang Ji:
Learning Local and Global Multi-context Representations for Document Classification. ICDM 2019: 1234-1239 - [c50]Hongyang Gao, Shuiwang Ji:
Graph U-Nets. ICML 2019: 2083-2092 - [c49]Jun Li, Yongjun Chen, Lei Cai, Ian Davidson, Shuiwang Ji:
Dense Transformer Networks for Brain Electron Microscopy Image Segmentation. IJCAI 2019: 2894-2900 - [c48]Hongyang Gao, Shuiwang Ji:
Graph Representation Learning via Hard and Channel-Wise Attention Networks. KDD 2019: 741-749 - [c47]Yin Zhang, Ninghao Liu, Shuiwang Ji, James Caverlee, Xia Hu:
An Interpretable Neural Model with Interactive Stepwise Influence. PAKDD (3) 2019: 528-540 - [c46]Lei Cai, Hongyang Gao, Shuiwang Ji:
Multi-Stage Variational Auto-Encoders for Coarse-to-Fine Image Generation. SDM 2019: 630-638 - [c45]Zhengyang Wang, Hao Yuan, Shuiwang Ji:
Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions. SDM 2019: 648-656 - [c44]Mengnan Du, Ninghao Liu, Fan Yang, Shuiwang Ji, Xia Hu:
On Attribution of Recurrent Neural Network Predictions via Additive Decomposition. WWW 2019: 383-393 - [c43]Hongyang Gao, Yongjun Chen, Shuiwang Ji:
Learning Graph Pooling and Hybrid Convolutional Operations for Text Representations. WWW 2019: 2743-2749 - [c42]Fan Yang, Shiva K. Pentyala, Sina Mohseni, Mengnan Du, Hao Yuan, Rhema Linder, Eric D. Ragan, Shuiwang Ji, Xia (Ben) Hu:
XFake: Explainable Fake News Detector with Visualizations. WWW 2019: 3600-3604 - [i17]Hongyang Gao, Yongjun Chen, Shuiwang Ji:
Learning Graph Pooling and Hybrid Convolutional Operations for Text Representations. CoRR abs/1901.06965 (2019) - [i16]Mengnan Du, Ninghao Liu, Fan Yang, Shuiwang Ji, Xia Hu:
On Attribution of Recurrent Neural Network Predictions via Additive Decomposition. CoRR abs/1903.11245 (2019) - [i15]Hongyang Gao, Shuiwang Ji:
Graph U-Nets. CoRR abs/1905.05178 (2019) - [i14]Yi Liu, Hao Yuan, Zhengyang Wang, Shuiwang Ji:
Global Transformer U-Nets for Label-Free Prediction of Fluorescence Images. CoRR abs/1907.00941 (2019) - [i13]Hongyang Gao, Shuiwang Ji:
Graph Representation Learning via Hard and Channel-Wise Attention Networks. CoRR abs/1907.04652 (2019) - [i12]Fan Yang, Shiva K. Pentyala, Sina Mohseni, Mengnan Du, Hao Yuan, Rhema Linder, Eric D. Ragan, Shuiwang Ji, Xia (Ben) Hu:
XFake: Explainable Fake News Detector with Visualizations. CoRR abs/1907.07757 (2019) - 2018
- [j38]Zhongyu Li, Erik Butler, Kang Li, Aidong Lu, Shuiwang Ji, Shaoting Zhang:
Large-scale Exploration of Neuronal Morphologies Using Deep Learning and Augmented Reality. Neuroinformatics 16(3-4): 339-349 (2018) - [j37]Lei Cai, Bian Wu, Shuiwang Ji:
Neuronal Activities in the Mouse Visual Cortex Predict Patterns of Sensory Stimuli. Neuroinformatics 16(3-4): 473-488 (2018) - [j36]Lei Zhang, Yao Zhao, Zhenfeng Zhu, Dinggang Shen, Shuiwang Ji:
Multi-View Missing Data Completion. IEEE Trans. Knowl. Data Eng. 30(7): 1296-1309 (2018) - [c41]Lei Cai, Zhengyang Wang, Hongyang Gao, Dinggang Shen, Shuiwang Ji:
Deep Adversarial Learning for Multi-Modality Missing Data Completion. KDD 2018: 1158-1166 - [c40]Yongjun Chen, Hongyang Gao, Lei Cai, Min Shi, Dinggang Shen, Shuiwang Ji:
Voxel Deconvolutional Networks for 3D Brain Image Labeling. KDD 2018: 1226-1234 - [c39]Hongyang Gao, Zhengyang Wang, Shuiwang Ji:
Large-Scale Learnable Graph Convolutional Networks. KDD 2018: 1416-1424 - [c38]Zhengyang Wang, Shuiwang Ji:
Smoothed Dilated Convolutions for Improved Dense Prediction. KDD 2018: 2486-2495 - [c37]Hongyang Gao, Zhengyang Wang, Shuiwang Ji:
ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions. NeurIPS 2018: 5203-5211 - [c36]Zhengyang Wang, Shuiwang Ji:
Learning Convolutional Text Representations for Visual Question Answering. SDM 2018: 594-602 - [i11]Hongyang Gao, Zhengyang Wang, Shuiwang Ji:
Large-Scale Learnable Graph Convolutional Networks. CoRR abs/1808.03965 (2018) - [i10]Zhengyang Wang, Shuiwang Ji:
Smoothed Dilated Convolutions for Improved Dense Prediction. CoRR abs/1808.08931 (2018) - [i9]Hongyang Gao, Zhengyang Wang, Shuiwang Ji:
ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions. CoRR abs/1809.01330 (2018) - [i8]Zhengyang Wang, Na Zou, Dinggang Shen, Shuiwang Ji:
Global Deep Learning Methods for Multimodality Isointense Infant Brain Image Segmentation. CoRR abs/1812.04103 (2018) - 2017
- [j35]Tao Zeng, Bian Wu, Shuiwang Ji:
DeepEM3D: approaching human-level performance on 3D anisotropic EM image segmentation. Bioinform. 33(16): 2555-2562 (2017) - [j34]Ahmed Fakhry, Tao Zeng, Shuiwang Ji:
Residual Deconvolutional Networks for Brain Electron Microscopy Image Segmentation. IEEE Trans. Medical Imaging 36(2): 447-456 (2017) - [j33]Rongjian Li, Tao Zeng, Hanchuan Peng, Shuiwang Ji:
Deep Learning Segmentation of Optical Microscopy Images Improves 3-D Neuron Reconstruction. IEEE Trans. Medical Imaging 36(7): 1533-1541 (2017) - [j32]Jie Gui, Zhenan Sun, Shuiwang Ji, Dacheng Tao, Tieniu Tan:
Feature Selection Based on Structured Sparsity: A Comprehensive Study. IEEE Trans. Neural Networks Learn. Syst. 28(7): 1490-1507 (2017) - [c35]Xia Hu, Shuiwang Ji:
IDM 2017: Workshop on Interpretable Data Mining - Bridging the Gap between Shallow and Deep Models. CIKM 2017: 2565-2566 - [c34]Debrup Banerjee, Kazi Aminul Islam, Gang Mei, Lemin Xiao, Guangfan Zhang, Roger Xu, Shuiwang Ji, Jiang Li:
A Deep Transfer Learning Approach for Improved Post-Traumatic Stress Disorder Diagnosis. ICDM 2017: 11-20 - [c33]Hongyang Gao, Shuiwang Ji:
Efficient and Invariant Convolutional Neural Networks for Dense Prediction. ICDM 2017: 871-876 - [c32]Tao Zeng, Bian Wu, Jiayu Zhou, Ian Davidson, Shuiwang Ji:
Recurrent Encoder-Decoder Networks for Time-Varying Dense Prediction. ICDM 2017: 1165-1170 - [c31]Qi Wang, Mengying Sun, Liang Zhan, Paul Thompson, Shuiwang Ji, Jiayu Zhou:
Multi-Modality Disease Modeling via Collective Deep Matrix Factorization. KDD 2017: 1155-1164 - [i7]Hongyang Gao, Hao Yuan, Zhengyang Wang, Shuiwang Ji:
Pixel Deconvolutional Networks. CoRR abs/1705.06820 (2017) - [i6]Zhengyang Wang, Hao Yuan, Shuiwang Ji:
Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions. CoRR abs/1705.06821 (2017) - [i5]Zhengyang Wang, Shuiwang Ji:
Learning Convolutional Text Representations for Visual Question Answering. CoRR abs/1705.06824 (2017) - [i4]Lei Cai, Hongyang Gao, Shuiwang Ji:
Multi-Stage Variational Auto-Encoders for Coarse-to-Fine Image Generation. CoRR abs/1705.07202 (2017) - [i3]Jun Li, Yongjun Chen, Lei Cai, Ian Davidson, Shuiwang Ji:
Dense Transformer Networks. CoRR abs/1705.08881 (2017) - [i2]Hongyang Gao, Shuiwang Ji:
Efficient and Invariant Convolutional Neural Networks for Dense Prediction. CoRR abs/1711.09064 (2017) - 2016
- [j31]Ahmed Fakhry, Hanchuan Peng, Shuiwang Ji:
Deep models for brain EM image segmentation: novel insights and improved performance. Bioinform. 32(15): 2352-2358 (2016) - [c30]Rongjian Li, Dong Si, Tao Zeng, Shuiwang Ji, Jing He:
Deep convolutional neural networks for detecting secondary structures in protein density maps from cryo-electron microscopy. BIBM 2016: 41-46 - [c29]Qingyang Li, Shuang Qiu, Shuiwang Ji, Paul M. Thompson, Jieping Ye, Jie Wang:
Parallel Lasso Screening for Big Data Optimization. KDD 2016: 1705-1714 - [c28]Kaixiang Lin, Jianpeng Xu, Inci M. Baytas, Shuiwang Ji, Jiayu Zhou:
Multi-Task Feature Interaction Learning. KDD 2016: 1735-1744 - [c27]Lei Zhang, Shupeng Wang, Xiaoyu Zhang, Yong Wang, Binbin Li, Dinggang Shen, Shuiwang Ji:
Collaborative Multi-View Denoising. KDD 2016: 2045-2054 - 2015
- [j30]Tao Zeng, Rongjian Li, Ravi Mukkamala, Jieping Ye, Shuiwang Ji:
Deep convolutional neural networks for annotating gene expression patterns in the mouse brain. BMC Bioinform. 16: 147:1-147:10 (2015) - [j29]Ahmed Fakhry, Tao Zeng, Hanchuan Peng, Shuiwang Ji:
Global analysis of gene expression and projection target correlations in the mouse brain. Brain Informatics 2(2): 107-117 (2015) - [j28]Wenlu Zhang, Rongjian Li, Daming Feng, Andrey N. Chernikov, Nikos Chrisochoides, Christopher Osgood, Shuiwang Ji:
Evolutionary soft co-clustering: formulations, algorithms, and applications. Data Min. Knowl. Discov. 29(3): 765-791 (2015) - [j27]Wenlu Zhang, Rongjian Li, Houtao Deng, Li Wang, Weili Lin, Shuiwang Ji, Dinggang Shen:
Deep convolutional neural networks for multi-modality isointense infant brain image segmentation. NeuroImage 108: 214-224 (2015) - [j26]Feng Li, Loc Tran, Kim-Han Thung, Shuiwang Ji, Dinggang Shen, Jiang Li:
A Robust Deep Model for Improved Classification of AD/MCI Patients. IEEE J. Biomed. Health Informatics 19(5): 1610-1616 (2015) - [j25]Rongjian Li, Wenlu Zhang, Yao Zhao, Zhenfeng Zhu, Shuiwang Ji:
Sparsity Learning Formulations for Mining Time-Varying Data. IEEE Trans. Knowl. Data Eng. 27(5): 1411-1423 (2015) - [c26]Tao Zeng, Shuiwang Ji:
Deep Convolutional Neural Networks for Multi-instance Multi-task Learning. ICDM 2015: 579-588 - [c25]Sen Yang, Qian Sun, Shuiwang Ji, Peter Wonka, Ian Davidson, Jieping Ye:
Structural Graphical Lasso for Learning Mouse Brain Connectivity. KDD 2015: 1385-1394 - [c24]Wenlu Zhang, Rongjian Li, Tao Zeng, Qian Sun, Sudhir Kumar, Jieping Ye, Shuiwang Ji:
Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis. KDD 2015: 1475-1484 - [c23]Tao Yang, Xinlin Zhao, Binbin Lin, Tao Zeng, Shuiwang Ji, Jieping Ye:
Automated Gene Expression Pattern Annotation in the Mouse Brain. Pacific Symposium on Biocomputing 2015: 144-155 - 2014
- [j24]Lei Yuan, Cheng Pan, Shuiwang Ji, Michael McCutchan, Zhi-Hua Zhou, Stuart J. Newfeld, Sudhir Kumar, Jieping Ye:
Automated annotation of developmental stages of Drosophila embryos in images containing spatial patterns of expression. Bioinform. 30(2): 266-273 (2014) - [j23]Rongjian Li, Wenlu Zhang, Shuiwang Ji:
Automated identification of cell-type-specific genes in the mouse brain by image computing of expression patterns. BMC Bioinform. 15: 209 (2014) - [j22]Shuiwang Ji, Ahmed Fakhry, Houtao Deng:
Integrative analysis of the connectivity and gene expression atlases in the mouse brain. NeuroImage 84: 245-253 (2014) - [j21]Jie Gui, Zhenan Sun, Jun Cheng, Shuiwang Ji, Xindong Wu:
How to Estimate the Regularization Parameter for Spectral Regression Discriminant Analysis and its Kernel Version? IEEE Trans. Circuits Syst. Video Technol. 24(2): 211-223 (2014) - [c22]Feng Li, Loc Tran, Kim-Han Thung, Shuiwang Ji, Dinggang Shen, Jiang Li:
Robust Deep Learning for Improved Classification of AD/MCI Patients. MLMI 2014: 240-247 - [c21]Rongjian Li, Wenlu Zhang, Heung-Il Suk, Li Wang, Jiang Li, Dinggang Shen, Shuiwang Ji:
Deep Learning Based Imaging Data Completion for Improved Brain Disease Diagnosis. MICCAI (3) 2014: 305-312 - 2013
- [j20]Shuiwang Ji:
Computational genetic neuroanatomy of the developing mouse brain: dimensionality reduction, visualization, and clustering. BMC Bioinform. 14: 222 (2013) - [j19]Qian Sun, Sherin Muckatira, Lei Yuan, Shuiwang Ji, Stuart J. Newfeld, Sudhir Kumar, Jieping Ye:
Image-level and group-level models for Drosophila gene expression pattern annotation. BMC Bioinform. 14: 350 (2013) - [j18]Wenlu Zhang, Daming Feng, Rongjian Li, Andrey N. Chernikov, Nikos Chrisochoides, Christopher Osgood, Charlotte Konikoff, Stuart J. Newfeld, Sudhir Kumar, Shuiwang Ji:
A mesh generation and machine learning framework for Drosophila gene expression pattern image analysis. BMC Bioinform. 14: 372 (2013) - [j17]Shuiwang Ji, Wei Xu, Ming Yang, Kai Yu:
3D Convolutional Neural Networks for Human Action Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 35(1): 221-231 (2013) - [j16]Shuiwang Ji, Wenlu Zhang, Rongjian Li:
A Probabilistic Latent Semantic Analysis Model for Coclustering the Mouse Brain Atlas. IEEE ACM Trans. Comput. Biol. Bioinform. 10(6): 1460-1468 (2013) - [j15]Xinhai Liu, Shuiwang Ji, Wolfgang Glänzel, Bart De Moor:
Multiview Partitioning via Tensor Methods. IEEE Trans. Knowl. Data Eng. 25(5): 1056-1069 (2013) - [c20]Shuiwang Ji, Wenlu Zhang, Rui Zhang:
Evolutionary Soft Co-Clustering. SDM 2013: 121-129 - 2012
- [j14]Lei Yuan, Alexander Woodard, Shuiwang Ji, Yuan Jiang, Zhi-Hua Zhou, Sudhir Kumar, Jieping Ye:
Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval. BMC Bioinform. 13: 107 (2012) - [j13]Jie Gui, Zhenan Sun, Wei Jia, Rong-Xiang Hu, Ying-Ke Lei, Shuiwang Ji:
Discriminant sparse neighborhood preserving embedding for face recognition. Pattern Recognit. 45(8): 2884-2893 (2012) - [j12]Ying-Xin Li, Shuiwang Ji, Sudhir Kumar, Jieping Ye, Zhi-Hua Zhou:
Drosophila Gene Expression Pattern Annotation through Multi-Instance Multi-Label Learning. IEEE ACM Trans. Comput. Biol. Bioinform. 9(1): 98-112 (2012) - [c19]Shuiwang Ji, Wenlu Zhang, Jun Liu:
A sparsity-inducing formulation for evolutionary co-clustering. KDD 2012: 334-342 - [i1]Jun Liu, Shuiwang Ji, Jieping Ye:
Multi-Task Feature Learning Via Efficient l2,1-Norm Minimization. CoRR abs/1205.2631 (2012) - 2011
- [j11]Shuiwang Ji:
Computational network analysis of the anatomical and genetic organizations in the mouse brain. Bioinform. 27(23): 3293-3299 (2011) - [j10]Sudhir Kumar, Charlotte Konikoff, Bernard Van Emden, Christopher Busick, Kailah T. Davis, Shuiwang Ji, Lin-Wei Wu, Hector Ramos, Thomas Brody, Sethuraman Panchanathan, Jieping Ye, Timothy L. Karr, Kristyn Gerold, Michael McCutchan, Stuart J. Newfeld:
FlyExpress: visual mining of spatiotemporal patterns for genes and publications in Drosophila embryogenesis. Bioinform. 27(23): 3319-3320 (2011) - [j9]Liang Sun, Shuiwang Ji, Jieping Ye:
Canonical Correlation Analysis for Multilabel Classification: A Least-Squares Formulation, Extensions, and Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 33(1): 194-200 (2011) - 2010
- [j8]Ting Kei Pong, Paul Tseng, Shuiwang Ji, Jieping Ye:
Trace Norm Regularization: Reformulations, Algorithms, and Multi-Task Learning. SIAM J. Optim. 20(6): 3465-3489 (2010) - [j7]Shuiwang Ji, Lei Tang, Shipeng Yu, Jieping Ye:
A shared-subspace learning framework for multi-label classification. ACM Trans. Knowl. Discov. Data 4(2): 8:1-8:29 (2010) - [c18]Shuiwang Ji, Wei Xu, Ming Yang, Kai Yu:
3D Convolutional Neural Networks for Human Action Recognition. ICML 2010: 495-502
2000 – 2009
- 2009
- [j6]Shuiwang Ji, Ying-Xin Li, Zhi-Hua Zhou, Sudhir Kumar, Jieping Ye:
A bag-of-words approach for Drosophila gene expression pattern annotation. BMC Bioinform. 10 (2009) - [c17]Shuiwang Ji, Jieping Ye:
An accelerated gradient method for trace norm minimization. ICML 2009: 457-464 - [c16]Liang Sun, Shuiwang Ji, Jieping Ye:
A least squares formulation for a class of generalized eigenvalue problems in machine learning. ICML 2009: 977-984 - [c15]Shuiwang Ji, Jieping Ye:
Linear Dimensionality Reduction for Multi-label Classification. IJCAI 2009: 1077-1082 - [c14]Liang Sun, Shuiwang Ji, Shipeng Yu, Jieping Ye:
On the Equivalence between Canonical Correlation Analysis and Orthonormalized Partial Least Squares. IJCAI 2009: 1230-1235 - [c13]Ying-Xin Li, Shuiwang Ji, Sudhir Kumar, Jieping Ye, Zhi-Hua Zhou:
DrosophilaGene Expression Pattern Annotation through Multi-Instance Multi-Label Learning. IJCAI 2009: 1445-1450 - [c12]Shuiwang Ji, Lei Yuan, Ying-Xin Li, Zhi-Hua Zhou, Sudhir Kumar, Jieping Ye:
Drosophila gene expression pattern annotation using sparse features and term-term interactions. KDD 2009: 407-416 - [c11]Bao-Hong Shen, Shuiwang Ji, Jieping Ye:
Mining discrete patterns via binary matrix factorization. KDD 2009: 757-766 - [c10]Ming Yang, Shuiwang Ji, Wei Xu, Jinjun Wang, Fengjun Lv, Kai Yu, Yihong Gong, Mert Dikmen, Dennis J. Lin, Thomas S. Huang:
Detecting Human Actions in Surveillance Videos. TRECVID 2009 - [c9]Jun Liu, Shuiwang Ji, Jieping Ye:
Multi-Task Feature Learning Via Efficient l2, 1-Norm Minimization. UAI 2009: 339-348 - 2008
- [j5]Shuiwang Ji, Liang Sun, Rong Jin, Sudhir Kumar, Jieping Ye:
Automated annotation of Drosophila gene expression patterns using a controlled vocabulary. Bioinform. 24(17): 1881-1888 (2008) - [j4]Liang Sun, Shuiwang Ji, Jieping Ye:
Adaptive diffusion kernel learning from biological networks for protein function prediction. BMC Bioinform. 9 (2008) - [j3]Jieping Ye, Shuiwang Ji, Jianhui Chen:
Multi-class Discriminant Kernel Learning via Convex Programming. J. Mach. Learn. Res. 9: 719-758 (2008) - [j2]Shuiwang Ji, Jieping Ye:
Kernel Uncorrelated and Regularized Discriminant Analysis: A Theoretical and Computational Study. IEEE Trans. Knowl. Data Eng. 20(10): 1311-1321 (2008) - [j1]Shuiwang Ji, Jieping Ye:
Generalized Linear Discriminant Analysis: A Unified Framework and Efficient Model Selection. IEEE Trans. Neural Networks 19(10): 1768-1782 (2008) - [c8]Shuiwang Ji, Jieping Ye:
A unified framework for generalized Linear Discriminant Analysis. CVPR 2008 - [c7]Liang Sun, Shuiwang Ji, Jieping Ye:
A least squares formulation for canonical correlation analysis. ICML 2008: 1024-1031 - [c6]Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Mingrui Wu, Jieping Ye:
Learning subspace kernels for classification. KDD 2008: 106-114 - [c5]Shuiwang Ji, Lei Tang, Shipeng Yu, Jieping Ye:
Extracting shared subspace for multi-label classification. KDD 2008: 381-389 - [c4]Liang Sun, Shuiwang Ji, Jieping Ye:
Hypergraph spectral learning for multi-label classification. KDD 2008: 668-676 - [c3]Shuiwang Ji, Liang Sun, Rong Jin, Jieping Ye:
Multi-label Multiple Kernel Learning. NIPS 2008: 777-784 - 2007
- [c2]Jieping Ye, Jianhui Chen, Shuiwang Ji:
Discriminant kernel and regularization parameter learning via semidefinite programming. ICML 2007: 1095-1102 - [c1]Jieping Ye, Shuiwang Ji, Jianhui Chen:
Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming. KDD 2007: 854-863
Coauthor Index
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