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ORCIDShuiwang Ji
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- affiliation: Old Dominion University, Norfolk, USA
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2020 – today
- 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) - [c94]Hongyi Ling, Zhimeng Jiang, Youzhi Luo, Shuiwang Ji, Na Zou:
Learning Fair Graph Representations via Automated Data Augmentations. ICLR 2023 - [c93]Meng Liu, Haoran Liu, Shuiwang Ji:
Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models. ICLR 2023 - [c92]Youzhi Luo, Michael McThrow, Wing Yee Au, Tao Komikado, Kanji Uchino, Koji Maruhashi, Shuiwang Ji:
Automated Data Augmentations for Graph Classification. ICLR 2023 - [c91]Limei Wang, Haoran Liu, Yi Liu, Jerry Kurtin, Shuiwang Ji:
Learning Hierarchical Protein Representations via Complete 3D Graph Networks. ICLR 2023 - [c90]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 - [c89]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 - [c88]Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji, Na Zou:
Graph Mixup with Soft Alignments. ICML 2023: 21335-21349 - [c87]Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji:
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian. ICML 2023: 40412-40424 - [c86]Minkai Xu, Meng Liu, Wengong Jin, Shuiwang Ji, Jure Leskovec, Stefano Ermon:
Graph and Geometry Generative Modeling for Drug Discovery. KDD 2023: 5833-5834 - [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]