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How Powerful are Spectral Graph Neural Networks

International Conference on Machine Learning (ICML), 2022

23 May 2022

Xiyuan Wang

Muhan Zhang

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Papers citing "How Powerful are Spectral Graph Neural Networks"

31 / 131 papers shown

Title
Spectral Heterogeneous Graph Convolutions via Positive Noncommutative PolynomialsThe Web Conference (WWW), 2023 Mingguo He Zhewei Wei Shi Feng Zhengjie Huang Weibin Li Yu Sun Dianhai Yu 338 13 0 31 May 2023
Revisiting Generalized p-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and Training with Non-Linear Diffusion Dai Shi Zhiqi Shao Yi Guo Qianchuan Zhao Junbin Gao 210 2 0 25 May 2023
A Fractional Graph Laplacian Approach to OversmoothingNeural Information Processing Systems (NeurIPS), 2023 Sohir Maskey Raffaele Paolino Aras Bacho Gitta Kutyniok 376 49 0 22 May 2023
Feature Expansion for Graph Neural NetworksInternational Conference on Machine Learning (ICML), 2023 Jiaqi Sun Lin Zhang Guan-Hong Chen Kun Zhang Peng Xu Yujiu Yang GNN 159 16 0 10 May 2023
Towards Better Graph Representation Learning with Parameterized Decomposition & FilteringInternational Conference on Machine Learning (ICML), 2023 Mingqi Yang Wenjie Feng Yanming Shen Bryan Hooi 287 5 0 10 May 2023
Beyond Homophily: Reconstructing Structure for Graph-agnostic ClusteringInternational Conference on Machine Learning (ICML), 2023 Erlin Pan Zhao Kang 137 59 0 03 May 2023
Who You Play Affects How You Play: Predicting Sports Performance Using Graph Attention Networks With Temporal Convolution Rui Luo Vikram Krishnamurthy 143 2 0 29 Mar 2023
LON-GNN: Spectral GNNs with Learnable Orthonormal Basis Qian Tao Zhen Wang Wenyuan Yu Yaliang Li Zhewei Wei 139 6 0 24 Mar 2023
Specformer: Spectral Graph Neural Networks Meet TransformersInternational Conference on Learning Representations (ICLR), 2023 Deyu Bo Chuan Shi Lele Wang Renjie Liao 259 124 0 02 Mar 2023
Graph Neural Networks with Learnable and Optimal Polynomial BasesInternational Conference on Machine Learning (ICML), 2023 Y. Guo Zhewei Wei 275 44 0 24 Feb 2023
A critical look at the evaluation of GNNs under heterophily: Are we really making progress?International Conference on Learning Representations (ICLR), 2023 Oleg Platonov Denis Kuznedelev Michael Diskin Artem Babenko Liudmila Prokhorenkova 241 305 0 22 Feb 2023
Diffusion Probabilistic Models for Structured Node ClassificationNeural Information Processing Systems (NeurIPS), 2023 Hyosoon Jang Seonghyun Park Sangwoo Mo SungSoo Ahn DiffM 294 5 0 21 Feb 2023
Efficiently Forgetting What You Have Learned in Graph Representation Learning via ProjectionInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023 Weilin Cong Mehrdad Mahdavi MU 94 23 0 17 Feb 2023
Robust Mid-Pass Filtering Graph Convolutional NetworksThe Web Conference (WWW), 2023 Jincheng Huang Lun Du Xu Chen Qiang Fu Shi Han Dongmei Zhang AAML 175 51 0 16 Feb 2023
A Survey on Spectral Graph Neural Networks Deyu Bo Xiao Wang Yang Liu Yuan Fang Yawen Li Chuan Shi 232 37 0 11 Feb 2023
Homophily modulates double descent generalization in graph convolution networksProceedings of the National Academy of Sciences of the United States of America (PNAS), 2022 Chengzhi Shi Liming Pan Hong Hu Ivan Dokmanić 345 12 0 26 Dec 2022
Node-oriented Spectral Filtering for Graph Neural NetworksIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022 Shuai Zheng Zhenfeng Zhu Zhizhe Liu Youru Li Yao-Min Zhao 221 23 0 07 Dec 2022
FakeEdge: Alleviate Dataset Shift in Link PredictionLOG IN (LOG IN), 2022 Kaiwen Dong Yijun Tian Zhichun Guo Yang Yang Nitesh Chawla 324 13 0 29 Nov 2022
Deep representation learning: Fundamentals, Perspectives, Applications, and Open Challenges K. T. Baghaei Amirreza Payandeh Pooya Fayyazsanavi Shahram Rahimi Zhiqian Chen Somayeh Bakhtiari Ramezani FaML AI4TS 203 10 0 27 Nov 2022
Graph Filters for Signal Processing and Machine Learning on GraphsIEEE Transactions on Signal Processing (IEEE Trans. Signal Process.), 2022 Elvin Isufi Fernando Gama D. Shuman Santiago Segarra GNN 209 117 0 16 Nov 2022
A Spectral Analysis of Graph Neural Networks on Dense and Sparse GraphsIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022 Luana Ruiz Ningyuan Huang Soledad Villar 204 6 0 06 Nov 2022
Improving Graph Neural Networks with Learnable Propagation OperatorsInternational Conference on Machine Learning (ICML), 2022 Moshe Eliasof Lars Ruthotto Eran Treister 200 26 0 31 Oct 2022
Clenshaw Graph Neural NetworksKnowledge Discovery and Data Mining (KDD), 2022 Y. Guo Zhewei Wei GNN 181 17 0 29 Oct 2022
Generalized energy and gradient flow via graph framelets Andi Han Dai Shi Zhiqi Shao Junbin Gao 271 15 0 08 Oct 2022
Graph Component Contrastive Learning for Concept Relatedness EstimationAAAI Conference on Artificial Intelligence (AAAI), 2022 Yueen Ma Zixing Song Xuming Hu Jingjing Li Yifei Zhang Irwin King 192 13 0 25 Jun 2022
How Powerful are K-hop Message Passing Graph Neural NetworksNeural Information Processing Systems (NeurIPS), 2022 Jiarui Feng Yixin Chen Fuhai Li Anindya Sarkar Muhan Zhang 239 146 0 26 May 2022
Convolutional Neural Networks on Graphs with Chebyshev Approximation, RevisitedNeural Information Processing Systems (NeurIPS), 2022 Mingguo He Zhewei Wei Ji-Rong Wen GNN 359 166 0 04 Feb 2022
MGNN: Graph Neural Networks Inspired by Distance Geometry ProblemKnowledge Discovery and Data Mining (KDD), 2022 Guanyu Cui Zhewei Wei 146 12 0 31 Jan 2022
Implicit vs Unfolded Graph Neural Networks Yongyi Yang Tang Liu Yangkun Wang Zengfeng Huang David Wipf 398 17 0 12 Nov 2021
Bridging the Gap between Spatial and Spectral Domains: A Unified Framework for Graph Neural NetworksACM Computing Surveys (CSUR), 2021 Zhiqian Chen Fanglan Chen Lei Zhang Taoran Ji Kaiqun Fu Bo Pan Feng Chen Lingfei Wu Charu C. Aggarwal Chang-Tien Lu 567 32 0 21 Jul 2021
Adaptive Universal Generalized PageRank Graph Neural NetworkInternational Conference on Learning Representations (ICLR), 2020 Eli Chien Jianhao Peng Pan Li O. Milenkovic 948 910 0 14 Jun 2020