BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation

21 June 2021

Papers citing "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"

50 / 136 papers shown

Title
Disambiguated Node Classification with Graph Neural Networks Tianxiang Zhao Xiang Zhang Suhang Wang AI4CE 26 2 0 13 Feb 2024
Large Language Model Meets Graph Neural Network in Knowledge Distillation Shengxiang Hu Guobing Zou Song Yang Yanglan Gan Bofeng Zhang Yixin Chen 46 7 0 08 Feb 2024
Multi-view Subspace Clustering via An Adaptive Consensus Graph Filter Lai Wei Shanshan Song 16 1 0 30 Jan 2024
DGNN: Decoupled Graph Neural Networks with Structural Consistency between Attribute and Graph Embedding Representations Jinlu Wang Jipeng Guo Yanfeng Sun Junbin Gao Shaofan Wang Yachao Yang Baocai Yin AI4CE 28 2 0 28 Jan 2024
Improving Expressive Power of Spectral Graph Neural Networks with Eigenvalue Correction Kangkang Lu Yanhua Yu Hao Fei Xuan Li Zixuan Yang Zirui Guo Meiyu Liang Mengran Yin Tat-Seng Chua 26 3 0 28 Jan 2024
LightDiC: A Simple yet Effective Approach for Large-scale Digraph Representation Learning Xunkai Li Meihao Liao Zhengyu Wu Daohan Su Wentao Zhang Ronghua Li Guoren Wang AI4CE 38 7 0 22 Jan 2024
Infinite-Horizon Graph Filters: Leveraging Power Series to Enhance Sparse Information Aggregation Ruizhe Zhang Xinke Jiang Yuchen Fang Jiayuan Luo Yongxin Xu Yichen Zhu Xu Chu Junfeng Zhao Yasha Wang 21 1 0 18 Jan 2024
Rethinking Spectral Graph Neural Networks with Spatially Adaptive Filtering Jingwei Guo Kaizhu Huang Xinping Yi Zixian Su Rui Zhang 24 3 0 17 Jan 2024
Data Augmentation for Supervised Graph Outlier Detection with Latent Diffusion Models Kay Liu Hengrui Zhang Ziqing Hu Fangxin Wang Philip S. Yu 29 1 0 29 Dec 2023
FCDNet: Frequency-Guided Complementary Dependency Modeling for Multivariate Time-Series Forecasting Weijun Chen Heyuan Wang Ye Tian Shijie Guan Ning Liu AI4TS 25 1 0 27 Dec 2023
PC-Conv: Unifying Homophily and Heterophily with Two-fold Filtering Bingheng Li Erlin Pan Zhao Kang 21 31 0 22 Dec 2023
Graph Neural Networks with Diverse Spectral Filtering Jingwei Guo Kaizhu Huang Xinping Yi Rui Zhang 56 12 0 14 Dec 2023
Curriculum-Enhanced Residual Soft An-Isotropic Normalization for Over-smoothness in Deep GNNs Jin Li Qirong Zhang Shuling Xu Xinlong Chen Longkun Guo Yanglan Fu 29 0 0 13 Dec 2023
Polynomial-based Self-Attention for Table Representation learning Jayoung Kim Yehjin Shin Jeongwhan Choi Hyowon Wi Noseong Park LMTD 21 2 0 12 Dec 2023
Breaking the Entanglement of Homophily and Heterophily in Semi-supervised Node Classification Henan Sun Xunkai Li Zhengyu Wu Daohan Su Ronghua Li Guoren Wang 34 12 0 07 Dec 2023
An Effective Universal Polynomial Basis for Spectral Graph Neural Networks Keke Huang Pietro Lió 16 1 0 30 Nov 2023
Graph Prompt Learning: A Comprehensive Survey and Beyond Xiangguo Sun Jiawen Zhang Xixi Wu Hong Cheng Yun Xiong Jia Li 25 51 0 28 Nov 2023
A Quasi-Wasserstein Loss for Learning Graph Neural Networks Minjie Cheng Hongteng Xu 25 1 0 18 Oct 2023
Equivariant Matrix Function Neural Networks Ilyes Batatia Lars L. Schaaf Huajie Chen Gábor Csányi Christoph Ortner Felix A. Faber 32 5 0 16 Oct 2023
Shape-aware Graph Spectral Learning Junjie Xu Enyan Dai Dongsheng Luo Xiang Zhang Suhang Wang 29 3 0 16 Oct 2023
Graph Distillation with Eigenbasis Matching Yang Liu Deyu Bo Chuan Shi DD 26 9 0 13 Oct 2023
Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection Xiangyu Dong Xingyi Zhang Sibo Wang GNN 24 14 0 04 Oct 2023
HoloNets: Spectral Convolutions do extend to Directed Graphs Christian Koke Daniel Cremers 36 9 0 03 Oct 2023
FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations C. Ekbote Ajinkya Deshpande Arun Shankar Iyer Ramakrishna Bairi Sundararajan Sellamanickam SSL 41 3 0 03 Oct 2023
NP $^2$ L: Negative Pseudo Partial Labels Extraction for Graph Neural Networks Xinjie Shen Danyang Wu Jitao Lu Junjie Liang Jin Xu Feiping Nie 33 0 0 02 Oct 2023
ResolvNet: A Graph Convolutional Network with multi-scale Consistency Christian Koke Abhishek Saroha Yuesong Shen Marvin Eisenberger Daniel Cremers GNN 22 1 0 30 Sep 2023
One for All: Towards Training One Graph Model for All Classification Tasks Hao Liu Jiarui Feng Lecheng Kong Ningyue Liang Dacheng Tao Yixin Chen Muhan Zhang AI4CE 15 110 0 29 Sep 2023
Higher-order Graph Convolutional Network with Flower-Petals Laplacians on Simplicial Complexes Yiming Huang Yujie Zeng Qiang Wu Linyuan Lu 27 18 0 22 Sep 2023
Language is All a Graph Needs Ruosong Ye Caiqi Zhang Runhui Wang Shuyuan Xu Yongfeng Zhang AI4CE 63 151 0 14 Aug 2023
How Curvature Enhance the Adaptation Power of Framelet GCNs Dai Shi Yi Guo Zhiqi Shao Junbin Gao 26 14 0 19 Jul 2023
Automated Polynomial Filter Learning for Graph Neural Networks Wendi Yu Zhichao Hou Xiaorui Liu 21 0 0 16 Jul 2023
Influential Simplices Mining via Simplicial Convolutional Network Yujie Zeng Yiming Huang Qiang Wu Linyuan Lu 19 10 0 11 Jul 2023
GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection Jianheng Tang Fengrui Hua Zi-Chao Gao P. Zhao Jia Li 25 55 0 21 Jun 2023
Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-prone Graphs Y. Zheng He Zhang V. Lee Yu Zheng Xiao Wang Shirui Pan 31 33 0 13 Jun 2023
On Manipulating Signals of User-Item Graph: A Jacobi Polynomial-based Graph Collaborative Filtering Jiayan Guo Lun Du Xu Chen Xiaojun Ma Qiang Fu Shi Han Dongmei Zhang Yan Zhang 23 19 0 06 Jun 2023
Clarify Confused Nodes via Separated Learning Jiajun Zhou Sheng Gong Chenxuan Xie Shanqing Yu Qi Xuan Xiaoniu Yang Xiaoniu Yang 81 3 0 04 Jun 2023
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? Haitao Mao Zhikai Chen Wei Jin Haoyu Han Yao Ma Tong Zhao Neil Shah Jiliang Tang 30 32 0 02 Jun 2023
Spectral Heterogeneous Graph Convolutions via Positive Noncommutative Polynomials Mingguo He Zhewei Wei Shi Feng Zhengjie Huang Weibin Li Yu Sun Dianhai Yu 26 6 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 34 1 0 25 May 2023
Self-Explainable Graph Neural Networks for Link Prediction Huaisheng Zhu Dongsheng Luo Xianfeng Tang Junjie Xu Hui Liu Suhang Wang 16 1 0 21 May 2023
Towards Understanding the Generalization of Graph Neural Networks Huayi Tang Y. Liu GNN AI4CE 32 29 0 14 May 2023
Feature Expansion for Graph Neural Networks Jiaqi Sun Lin Zhang Guan-Hong Chen Kun Zhang Peng Xu Yujiu Yang GNN 17 13 0 10 May 2023
Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering Mingqi Yang Wenjie Feng Yanming Shen Bryan Hooi 33 5 0 10 May 2023
LSGNN: Towards General Graph Neural Network in Node Classification by Local Similarity Yuhan Chen Yihong Luo Jing Tang Liang Yang Si-Huang Qiu Chuan Wang Xiaochun Cao 19 16 0 07 May 2023
Beyond Homophily: Reconstructing Structure for Graph-agnostic Clustering Erlin Pan Zhao Kang 29 35 0 03 May 2023
When Do Graph Neural Networks Help with Node Classification? Investigating the Impact of Homophily Principle on Node Distinguishability Sitao Luan Chenqing Hua Minkai Xu Qincheng Lu Jiaqi Zhu Xiaoming Chang Jie Fu J. Leskovec Doina Precup 38 3 0 25 Apr 2023
LON-GNN: Spectral GNNs with Learnable Orthonormal Basis Qian Tao Zhen Wang Wenyuan Yu Yaliang Li Zhewei Wei 27 5 0 24 Mar 2023
Specformer: Spectral Graph Neural Networks Meet Transformers Deyu Bo Chuan Shi Lele Wang Renjie Liao 71 80 0 02 Mar 2023
Graph Neural Networks with Learnable and Optimal Polynomial Bases Y. Guo Zhewei Wei 32 29 0 24 Feb 2023
Robust Mid-Pass Filtering Graph Convolutional Networks Jincheng Huang Lun Du Xu Chen Qiang Fu Shi Han Dongmei Zhang AAML 24 34 0 16 Feb 2023