Title
Framework GNN-AID: Graph Neural Network Analysis Interpretation and Defense Kirill Lukyanov Mikhail Drobyshevskiy Georgii Sazonov Mikhail Soloviov Ilya Makarov GNN 46 0 0 06 May 2025
RISE: Radius of Influence based Subgraph Extraction for 3D Molecular Graph Explanation J. Qu Wenhan Gao Jiaxing Zhang Xufeng Liu Hua Wei Haibin Ling Y. Liu AI4CE 52 0 0 04 May 2025
PyGDA: A Python Library for Graph Domain Adaptation Zhen Zhang Meihan Liu Bingsheng He AI4CE OOD 49 0 0 13 Mar 2025
Beyond Euclid: An Illustrated Guide to Modern Machine Learning with Geometric, Topological, and Algebraic Structures Sophia Sanborn Johan Mathe Mathilde Papillon Domas Buracas Hansen Lillemark Christian Shewmake Abby Bertics Xavier Pennec Nina Miolane 58 4 0 12 Jul 2024
Complete and Efficient Graph Transformers for Crystal Material Property Prediction Keqiang Yan Cong Fu Xiaofeng Qian Xiaoning Qian Shuiwang Ji 41 19 0 18 Mar 2024
A Differential Geometric View and Explainability of GNN on Evolving Graphs Yazheng Liu Xi Zhang Sihong Xie 19 3 0 11 Mar 2024
PPFlow: Target-aware Peptide Design with Torsional Flow Matching Haitao Lin Odin Zhang Huifeng Zhao Dejun Jiang Lirong Wu Zicheng Liu Yufei Huang Stan Z. Li 49 12 0 05 Mar 2024
Unsupervised Optimisation of GNNs for Node Clustering Will Leeney Ryan McConville 31 0 0 12 Feb 2024
On Discprecncies between Perturbation Evaluations of Graph Neural Network Attributions Razieh Rezaei Alireza Dizaji Ashkan Khakzar Anees Kazi Nassir Navab Daniel Rueckert 21 0 0 01 Jan 2024
PerCNet: Periodic Complete Representation for Crystal Graphs Jiao Huang Qianli Xing Jinglong Ji Bo Yang 34 1 0 03 Dec 2023
PyTorch Geometric High Order: A Unified Library for High Order Graph Neural Network Xiyuan Wang Muhan Zhang AI4CE 13 3 0 28 Nov 2023
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Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks Xu Zheng Farhad Shirani Tianchun Wang Wei Cheng Zhuomin Chen Haifeng Chen Hua Wei Dongsheng Luo 27 11 0 03 Oct 2023
On the Robustness of Post-hoc GNN Explainers to Label Noise Zhiqiang Zhong Yangqianzi Jiang Davide Mottin AAML NoLa 29 3 0 04 Sep 2023
Will More Expressive Graph Neural Networks do Better on Generative Tasks? Xian-Quan Zou Xiangyu Zhao Pietro Lio' Yiren Zhao 15 2 0 23 Aug 2023
XFlow: Benchmarking Flow Behaviors over Graphs Zijian Zhang Zonghan Zhang Zhiqian Chen 30 0 0 07 Aug 2023
With Flying Colors: Predicting Community Success in Large-scale Collaborative Campaigns Abraham Israeli Oren Tsur 25 2 0 18 Jul 2023
Towards Symmetry-Aware Generation of Periodic Materials Youzhi Luo Chengkai Liu Shuiwang Ji DiffM 26 21 0 06 Jul 2023
Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks Gao Li M. Duda X. Zhang Danai Koutra Yujun Yan 13 8 0 26 Jun 2023
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules Haiyang Yu Meng Liu Youzhi Luo A. Strasser X. Qian Xiaoning Qian Shuiwang Ji 15 20 0 15 Jun 2023
Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials Shengchao Liu Weitao Du Yanjing Li Zhuoxinran Li Zhiling Zheng ... Anima Anandkumar C. Borgs J. Chayes Hongyu Guo Jian Tang AI4CE 33 19 0 15 Jun 2023
Graph Structure and Feature Extrapolation for Out-of-Distribution Generalization Xiner Li Shurui Gui Youzhi Luo Shuiwang Ji OODD OOD 20 10 0 13 Jun 2023
LibAUC: A Deep Learning Library for X-Risk Optimization Zhuoning Yuan Dixian Zhu Zimeng Qiu Gang Li Xuanhui Wang Tianbao Yang BDL 43 16 0 05 Jun 2023
Message-passing selection: Towards interpretable GNNs for graph classification Wen-Ding Li Kaixuan Chen Shunyu Liu Wenjie Huang Haofei Zhang Yingjie Tian Yun Su Mingli Song 25 1 0 03 Jun 2023
Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization Shurui Gui Meng Liu Xiner Li Youzhi Luo Shuiwang Ji CML OOD 23 24 0 01 Jun 2023
Improving Expressivity of GNNs with Subgraph-specific Factor Embedded Normalization Kaixuan Chen Shunyu Liu Tongtian Zhu Tongya Zheng Haofei Zhang Zunlei Feng Jingwen Ye Mingli Song 37 14 0 31 May 2023
Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaboration Haitao Lin Yufei Huang Haotian Zhang Lirong Wu Siyuan Li Zhiyuan Chen Stan Z. Li DiffM 14 23 0 30 May 2023
DEGREE: Decomposition Based Explanation For Graph Neural Networks Qizhang Feng Ninghao Liu Fan Yang Ruixiang Tang Mengnan Du Xia Hu 23 22 0 22 May 2023
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 DiffM 18 31 0 06 May 2023
A new perspective on building efficient and expressive 3D equivariant graph neural networks Weitao Du Yuanqi Du Limei Wang Dieqiao Feng Guifeng Wang Shuiwang Ji Carla P. Gomes Zhixin Ma AI4CE 27 33 0 07 Apr 2023
Towards Better Dynamic Graph Learning: New Architecture and Unified Library Le Yu Leilei Sun Bowen Du Weifeng Lv AI4CE 24 96 0 23 Mar 2023
Instance-incremental Scene Graph Generation from Real-world Point Clouds via Normalizing Flows Chao Qi Jianqin Yin Jinghang Xu Pengxiang Ding 3DPC 35 4 0 21 Feb 2023
Structural Explanations for Graph Neural Networks using HSIC Ayato Toyokuni Makoto Yamada 19 1 0 04 Feb 2023
A Network Science perspective of Graph Convolutional Networks: A survey Mingshan Jia Bogdan Gabrys Katarzyna Musial GNN 32 7 0 12 Jan 2023
Graph Learning Indexer: A Contributor-Friendly and Metadata-Rich Platform for Graph Learning Benchmarks Jiaqi Ma Xingjian Zhang Hezheng Fan Jin Huang Tianyue Li Tinghong Li Yiwen Tu Chen Zhu Qiaozhu Mei 35 5 0 08 Dec 2022
DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding Haitao Lin Yufei Huang Odin Zhang Siqi Ma Meng Liu X. Li Lirong Wu Shuiwang Ji Tingjun Hou Stan Z. Li DiffM 18 60 0 21 Nov 2022
Distributed Graph Neural Network Training: A Survey Yingxia Shao Hongzheng Li Xizhi Gu Hongbo Yin Yawen Li Xupeng Miao Wentao Zhang Bin Cui Lei Chen GNN AI4CE 11 56 0 01 Nov 2022
L2XGNN: Learning to Explain Graph Neural Networks G. Serra Mathias Niepert 31 7 0 28 Sep 2022
Periodic Graph Transformers for Crystal Material Property Prediction Keqiang Yan Yi Liu Yu-Ching Lin Shuiwang Ji AI4TS 88 84 0 23 Sep 2022
Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis Xuanyuan Han Pietro Barbiero Dobrik Georgiev Lucie Charlotte Magister Pietro Lió MILM 34 41 0 22 Aug 2022
Evaluating Explainability for Graph Neural Networks Chirag Agarwal Owen Queen Himabindu Lakkaraju Marinka Zitnik 38 99 0 19 Aug 2022
Learning Hierarchical Protein Representations via Complete 3D Graph Networks Limei Wang Haoran Liu Yi Liu Jerry Kurtin Shuiwang Ji GNN 28 55 0 26 Jul 2022
Graph Generative Model for Benchmarking Graph Neural Networks Minji Yoon Yue Wu John Palowitch Bryan Perozzi Ruslan Salakhutdinov 17 7 0 10 Jul 2022
FlowX: Towards Explainable Graph Neural Networks via Message Flows Shurui Gui Hao Yuan Jie Wang Qicheng Lao Kang Li Shuiwang Ji 32 11 0 26 Jun 2022
ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs Limei Wang Yi Liu Yu-Ching Lin Hao Liu Shuiwang Ji GNN 38 89 0 17 Jun 2022
GOOD: A Graph Out-of-Distribution Benchmark Shurui Gui Xiner Li Limei Wang Shuiwang Ji OOD 22 115 0 16 Jun 2022
GraphFM: Improving Large-Scale GNN Training via Feature Momentum Haiyang Yu Limei Wang Bokun Wang Meng Liu Tianbao Yang Shuiwang Ji GNN AI4CE 29 39 0 14 Jun 2022
3D Graph Contrastive Learning for Molecular Property Prediction Kisung Moon Sunyoung Kwon 13 17 0 31 May 2022
Faithful Explanations for Deep Graph Models Zifan Wang Yuhang Yao Chaoran Zhang Han Zhang Youjie Kang Carlee Joe-Wong Matt Fredrikson Anupam Datta FAtt 14 2 0 24 May 2022
Generating 3D Molecules for Target Protein Binding Meng Liu Youzhi Luo Kanji Uchino Koji Maruhashi Shuiwang Ji 16 112 0 19 Apr 2022