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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"

50 / 131 papers shown

Title
A Comprehensive Benchmark on Spectral GNNs: The Impact on Efficiency, Memory, and Effectiveness Ningyi Liao Haoyu Liu Zulun Zhu Siqiang Luo L. Lakshmanan 362 2 0 14 Jun 2024
fKAN: Fractional Kolmogorov-Arnold Networks with trainable Jacobi basis functions Alireza Afzal Aghaei 177 79 0 11 Jun 2024
What Can We Learn from State Space Models for Machine Learning on Graphs? Yinan Huang Siqi Miao Pan Li 205 11 0 09 Jun 2024
On the Expressive Power of Spectral Invariant Graph Neural NetworksInternational Conference on Machine Learning (ICML), 2024 Bohang Zhang Lingxiao Zhao Haggai Maron 211 16 0 06 Jun 2024
Equivariant Machine Learning on Graphs with Nonlinear Spectral Filters Ya-Wei Eileen Lin Ronen Talmon Ron Levie 235 1 0 03 Jun 2024
Spatio-Spectral Graph Neural Networks Simon Geisler Arthur Kosmala Daniel Herbst Stephan Günnemann 303 15 0 29 May 2024
Differentiable Cluster Graph Neural Network Yanfei Dong Mohammed Haroon Dupty Lambert Deng Zhuanghua Liu Yong Liang Goh Wee Sun Lee GNN 178 2 0 25 May 2024
Bundle Neural Networks for message diffusion on graphs Jacob Bamberger Federico Barbero Xiaowen Dong Michael M. Bronstein 315 8 0 24 May 2024
HC-GAE: The Hierarchical Cluster-based Graph Auto-Encoder for Graph Representation LearningNeural Information Processing Systems (NeurIPS), 2024 Zhuo Xu Lu Bai Lixin Cui Ming Li Yue Wang Edwin R. Hancock GNN 124 5 0 23 May 2024
Understanding Virtual Nodes: Oversquashing and Node Heterogeneity Joshua Southern Francesco Di Giovanni Michael M. Bronstein J. Lutzeyer 504 1 0 22 May 2024
A General Graph Spectral Wavelet Convolution via Chebyshev Order Decomposition Nian Liu Xiaoxin He T. Laurent Francesco Di Giovanni Michael M. Bronstein Xavier Bresson 269 1 0 22 May 2024
How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing Keke Huang Yu Guang Wang Ming Li Pietro Lio 217 52 0 21 May 2024
CKGConv: General Graph Convolution with Continuous Kernels Liheng Ma Soumyasundar Pal Yitian Zhang Jiaming Zhou Yingxue Zhang Mark Coates 184 8 0 21 Apr 2024
Rethinking the Graph Polynomial Filter via Positive and Negative Coupling Analysis Haodong Wen Bodong Du Ruixun Liu Deyu Meng Xiangyong Cao 218 0 0 16 Apr 2024
Polynomial Selection in Spectral Graph Neural Networks: An Error-Sum of Function Slices Approach Guoming Li Jian Yang Shangsong Liang Dongsheng Luo 303 0 0 15 Apr 2024
Spectral GNN via Two-dimensional (2-D) Graph Convolution Guoming Li Jian Yang Shangsong Liang Dongsheng Luo GNN 191 3 0 06 Apr 2024
Gegenbauer Graph Neural Networks for Time-varying Signal Reconstruction Jhon A. Castro-Correa Jhony H. Giraldo Mohsen Badiey Fragkiskos D. Malliaros 297 24 0 28 Mar 2024
Contextualized Messages Boost Graph Representations Brian Godwin Lim Galvin Brice Lim Renzo Roel Tan Kazushi Ikeda AI4CE 476 4 0 19 Mar 2024
Optimizing Polynomial Graph Filters: A Novel Adaptive Krylov Subspace ApproachThe Web Conference (WWW), 2024 Keke Huang Wencai Cao Hoang Ta Xiaokui Xiao Pietro Lio 309 8 0 12 Mar 2024
Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic GraphsInternational Conference on Machine Learning (ICML), 2024 M. Park Jaeseung Heo Dongwoo Kim 192 5 0 11 Mar 2024
Spectral Invariant Learning for Dynamic Graphs under Distribution ShiftsNeural Information Processing Systems (NeurIPS), 2024 Zeyang Zhang Xin Eric Wang Ziwei Zhang Zhou Qin Weigao Wen Hui Xue Haoyang Li Wenwu Zhu OOD 241 33 0 08 Mar 2024
BloomGML: Graph Machine Learning through the Lens of Bilevel OptimizationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024 Amber Yijia Zheng Tong He Yixuan Qiu Minjie Wang David Wipf 268 2 0 07 Mar 2024
Simplified PCNet with Robustness Bingheng Li Xuanting Xie Haoxiang Lei Ruiyi Fang Zhao Kang 301 9 0 06 Mar 2024
Representation Learning on Heterophilic Graph with Directional Neighborhood Attention Qincheng Lu Jiaqi Zhu Sitao Luan Xiaomeng Chang 135 7 0 03 Mar 2024
Graph Learning with Distributional Edge Layouts Xinjian Zhao Chaolong Ying Tianshu Yu 210 4 0 26 Feb 2024
Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs Anson Bastos Kuldeep Singh Abhishek Nadgeri Manish Singh Toyotaro Suzumura 141 2 0 25 Feb 2024
Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective Soo Yong Lee Sunwoo Kim Fanchen Bu Jaemin Yoo Jiliang Tang Kijung Shin 328 10 0 07 Feb 2024
Deep Frequency-Aware Functional Maps for Robust Shape Matching Feifan Luo Qinsong Li Ling Hu Haibo Wang Xinru Liu Shengjun Liu Hongyang Chen 207 0 0 06 Feb 2024
HGAttack: Transferable Heterogeneous Graph Adversarial Attack He Zhao Zhiwei Zeng Yongwei Wang Deheng Ye Chunyan Miao AAML 199 9 0 18 Jan 2024
Rethinking Spectral Graph Neural Networks with Spatially Adaptive Filtering Jingwei Guo Kaizhu Huang Xinping Yi Zixian Su Rui Zhang 258 4 0 17 Jan 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook Wenzhao Jiang Hao Liu Hui Xiong CML AI4CE 483 10 0 19 Dec 2023
Graph Neural Networks with Diverse Spectral FilteringThe Web Conference (WWW), 2023 Jingwei Guo Kaizhu Huang Xinping Yi Rui Zhang 333 14 0 14 Dec 2023
Breaking the Entanglement of Homophily and Heterophily in Semi-supervised Node Classification Henan Sun Miao Hu Zhengyu Wu Daohan Su Ronghua Li Guoren Wang 172 19 0 07 Dec 2023
An Effective Universal Polynomial Basis for Spectral Graph Neural Networks Keke Huang Pietro Lio 351 1 0 30 Nov 2023
Weakly supervised cross-modal learning in high-content screening Gabriel Watkinson Ethan O. Cohen Nicolas Bourriez Ihab Bendidi Guillaume Bollot Auguste Genovesio 159 4 0 08 Nov 2023
Graph Deep Learning for Time Series ForecastingACM Computing Surveys (ACM Comput. Surv.), 2023 Andrea Cini Ivan Marisca Daniele Zambon Cesare Alippi AI4TS AI4CE 400 27 0 24 Oct 2023
Heterogeneous Graph Neural Networks for End-to-End Traffic Assignment and Traffic Flow Learning Tong Liu Hadi Meidani 166 0 0 19 Oct 2023
Architectural Implications of GNN Aggregation Programming AbstractionsIEEE computer architecture letters (CAL), 2023 Yingjie Qi Jianlei Yang Ao Zhou Tong Qiao Chunming Hu GNN AI4CE 265 8 0 18 Oct 2023
Equivariant Matrix Function Neural NetworksInternational Conference on Learning Representations (ICLR), 2023 Ilyes Batatia Lars L. Schaaf Huajie Chen Gábor Csányi Christoph Ortner Felix A. Faber 354 9 0 16 Oct 2023
Shape-aware Graph Spectral Learning Junjie Xu Enyan Dai Dongsheng Luo Xiang Zhang Suhang Wang 234 4 0 16 Oct 2023
How Graph Neural Networks Learn: Lessons from Training DynamicsInternational Conference on Machine Learning (ICML), 2023 Chenxiao Yang Qitian Wu David Wipf Ruoyu Sun Junchi Yan AI4CE GNN 420 2 0 08 Oct 2023
HoloNets: Spectral Convolutions do extend to Directed GraphsInternational Conference on Learning Representations (ICLR), 2023 Christian Koke Zorah Lähner 335 19 0 03 Oct 2023
Label Deconvolution for Node Representation Learning on Large-scale Attributed Graphs against Learning BiasIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023 Zhihao Shi Jie Wang Fanghua Lu Hanzhu Chen Defu Lian Zheng Wang Jieping Ye Feng Wu AI4CE 226 7 0 26 Sep 2023
Higher-order Graph Convolutional Network with Flower-Petals Laplacians on Simplicial ComplexesAAAI Conference on Artificial Intelligence (AAAI), 2023 Yiming Huang Yujie Zeng Qiang Wu Linyuan Lu 149 26 0 22 Sep 2023
Deep Prompt Tuning for Graph Transformers Reza Shirkavand Heng-Chiao Huang 185 9 0 18 Sep 2023
Influential Simplices Mining via Simplicial Convolutional NetworkInformation Processing & Management (IPM), 2023 Yujie Zeng Yiming Huang Qiang Wu Linyuan Lu 143 13 0 11 Jul 2023
Evolving Computation Graphs Andreea Deac Jian Tang 184 1 0 22 Jun 2023
On Manipulating Signals of User-Item Graph: A Jacobi Polynomial-based Graph Collaborative FilteringKnowledge Discovery and Data Mining (KDD), 2023 Jiayan Guo Lun Du Xu Chen Xiaojun Ma Qiang Fu Shi Han Dongmei Zhang Yan Zhang 284 25 0 06 Jun 2023
Personalized Federated Domain Adaptation for Item-to-Item RecommendationConference on Uncertainty in Artificial Intelligence (UAI), 2023 Ziwei Fan Hao Ding Hao Ding T. Hoang 206 8 0 05 Jun 2023
Towards Deep Attention in Graph Neural Networks: Problems and RemediesInternational Conference on Machine Learning (ICML), 2023 Soo Yong Lee Fanchen Bu Jaemin Yoo Kijung Shin GNN 158 39 0 04 Jun 2023

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How Powerful are Spectral Graph Neural Networks

Papers citing "How Powerful are Spectral Graph Neural Networks"