On Provable Benefits of Depth in Training Graph Convolutional Networks

28 October 2021

Papers citing "On Provable Benefits of Depth in Training Graph Convolutional Networks"

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Title
Statistical physics analysis of graph neural networks: Approaching optimality in the contextual stochastic block model O. Duranthon L. Zdeborová 41 0 0 03 Mar 2025
UPL: Uncertainty-aware Pseudo-labeling for Imbalance Transductive Node Classification Mohammad T. Teimuri Zahra Dehghanian Gholamali Aminian Hamid R. Rabiee 47 0 0 02 Feb 2025
GFT: Graph Foundation Model with Transferable Tree Vocabulary Zehong Wang Zheyuan Zhang Nitesh V. Chawla Chuxu Zhang Yanfang Ye 34 9 0 09 Nov 2024
Rethinking Node Representation Interpretation through Relation Coherence Ying-Chun Lin Jennifer Neville Cassiano Becker Purvanshi Metha Nabiha Asghar Vipul Agarwal 21 0 0 01 Nov 2024
Towards Bridging Generalization and Expressivity of Graph Neural Networks Shouheng Li Floris Geerts Dongwoo Kim Qing Wang 23 1 0 14 Oct 2024
Improving Node Representation by Boosting Target-Aware Contrastive Loss Ying-Chun Lin Jennifer Neville SSL 15 0 0 04 Oct 2024
Learning Personalized Scoping for Graph Neural Networks under Heterophily Gangda Deng Hongkuan Zhou R. Kannan Viktor Prasanna 31 0 0 11 Sep 2024
Generalization of Geometric Graph Neural Networks Zhiyang Wang J. Cerviño Alejandro Ribeiro 19 2 0 08 Sep 2024
Beyond Over-smoothing: Uncovering the Trainability Challenges in Deep Graph Neural Networks Jie Peng Runlin Lei Zhewei Wei 13 4 0 07 Aug 2024
Foundations and Frontiers of Graph Learning Theory Yu Huang Min Zhou Menglin Yang Zhen Wang Muhan Zhang Jie Wang Hong Xie Hao Wang Defu Lian Enhong Chen AI4CE GNN 43 2 0 03 Jul 2024
Bridging Smoothness and Approximation: Theoretical Insights into Over-Smoothing in Graph Neural Networks Guangrui Yang Jianfei Li Ming Li Han Feng Ding-Xuan Zhou 28 1 0 01 Jul 2024
A Manifold Perspective on the Statistical Generalization of Graph Neural Networks Zhiyang Wang J. Cerviño Alejandro Ribeiro AI4CE GNN 23 5 0 07 Jun 2024
What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding Hongkang Li Meng Wang Tengfei Ma Sijia Liu Zaixi Zhang Pin-Yu Chen MLT AI4CE 37 10 0 04 Jun 2024
GATE: How to Keep Out Intrusive Neighbors Nimrah Mustafa R. Burkholz 28 0 0 01 Jun 2024
A Survey of Large Language Models on Generative Graph Analytics: Query, Learning, and Applications Wenbo Shang Xin Huang 24 9 0 23 Apr 2024
Generalization of Graph Neural Networks through the Lens of Homomorphism Shouheng Li Dongwoo Kim Qing Wang 26 1 0 10 Mar 2024
Generalization Error of Graph Neural Networks in the Mean-field Regime Gholamali Aminian Yixuan He G. Reinert Lukasz Szpruch Samuel N. Cohen 33 3 0 10 Feb 2024
Asymptotic generalization error of a single-layer graph convolutional network O. Duranthon L. Zdeborová MLT 35 2 0 06 Feb 2024
GGNNs : Generalizing GNNs using Residual Connections and Weighted Message Passing Abhinav Raghuvanshi K. Malleshappa AI4CE GNN 15 0 0 26 Nov 2023
Information-Theoretic Generalization Bounds for Transductive Learning and its Applications Huayi Tang Yong Liu 48 1 0 08 Nov 2023
Are GATs Out of Balance? Nimrah Mustafa Aleksandar Bojchevski R. Burkholz 41 4 0 11 Oct 2023
How Graph Neural Networks Learn: Lessons from Training Dynamics Chenxiao Yang Qitian Wu David Wipf Ruoyu Sun Junchi Yan AI4CE GNN 14 1 0 08 Oct 2023
TFE-GNN: A Temporal Fusion Encoder Using Graph Neural Networks for Fine-grained Encrypted Traffic Classification Haozhen Zhang Le Yu Xi Xiao Qing Li F. Mercaldo Xiapu Luo Qixu Liu 11 48 0 31 Jul 2023
Optimal Inference in Contextual Stochastic Block Models O. Duranthon L. Zdeborová BDL 35 8 0 06 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 21 31 0 02 Jun 2023
Towards Understanding the Generalization of Graph Neural Networks Huayi Tang Y. Liu GNN AI4CE 29 29 0 14 May 2023
Decouple Graph Neural Networks: Train Multiple Simple GNNs Simultaneously Instead of One Hongyuan Zhang Yanan Zhu Xuelong Li 10 7 0 20 Apr 2023
Do We Really Need Complicated Model Architectures For Temporal Networks? Weilin Cong Si Zhang Jian Kang Baichuan Yuan Hao Wu Xin Zhou Hanghang Tong Mehrdad Mahdavi GNN AI4TS 19 113 0 22 Feb 2023
Efficiently Forgetting What You Have Learned in Graph Representation Learning via Projection Weilin Cong Mehrdad Mahdavi MU 11 17 0 17 Feb 2023
Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks Shuai Zhang M. Wang Pin-Yu Chen Sijia Liu Songtao Lu Miaoyuan Liu MLT 11 16 0 06 Feb 2023
Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing Yunchong Song Cheng Zhou Xinbing Wang Zhouhan Lin 16 61 0 03 Feb 2023
Understanding and Improving Deep Graph Neural Networks: A Probabilistic Graphical Model Perspective Jiayuan Chen Xiang Zhang Yinfei Xu Tianli Zhao Renjie Xie Wei Xu GNN BDL 21 0 0 25 Jan 2023
Generative Graph Neural Networks for Link Prediction Xingping Xian Tao Wu Xiaoke Ma Shaojie Qiao Yabin Shao Chao Wang Lin Yuan Yuehua Wu AI4CE 17 4 0 31 Dec 2022
Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs Chenxiao Yang Qitian Wu Jiahua Wang Junchi Yan AI4CE 10 51 0 18 Dec 2022
A Simple Hypergraph Kernel Convolution based on Discounted Markov Diffusion Process Fuyang Li Jiying Zhang Xi Xiao Bin Zhang Dijun Luo 11 3 0 30 Oct 2022
Predicting Protein-Ligand Binding Affinity with Equivariant Line Graph Network Yi Yi Xu Wan Kangfei Zhao Ou-Yang Le Pei-Ying Zhao 10 1 0 27 Oct 2022
Analysis of Convolutions, Non-linearity and Depth in Graph Neural Networks using Neural Tangent Kernel Mahalakshmi Sabanayagam P. Esser D. Ghoshdastidar 18 2 0 18 Oct 2022
Old can be Gold: Better Gradient Flow can Make Vanilla-GCNs Great Again Ajay Jaiswal Peihao Wang Tianlong Chen Justin F. Rousseau Ying Ding Zhangyang Wang 14 10 0 14 Oct 2022
ASGNN: Graph Neural Networks with Adaptive Structure Zepeng Zhang Songtao Lu Zengfeng Huang Ziping Zhao AAML 36 1 0 03 Oct 2022
Equivariant Hypergraph Diffusion Neural Operators Peihao Wang Shenghao Yang Yunyu Liu Zhangyang Wang Pan Li DiffM 16 33 0 14 Jul 2022
Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling Hongkang Li M. Wang Sijia Liu Pin-Yu Chen Jinjun Xiong GNN 14 27 0 07 Jul 2022
Towards Understanding Graph Neural Networks: An Algorithm Unrolling Perspective Zepeng Zhang Ziping Zhao AI4CE 20 4 0 09 Jun 2022
Model Degradation Hinders Deep Graph Neural Networks Wentao Zhang Zeang Sheng Ziqi Yin Yuezihan Jiang Yikuan Xia Jun Gao Zhi-Xin Yang Bin Cui GNN AI4CE 16 39 0 09 Jun 2022
Universal Deep GNNs: Rethinking Residual Connection in GNNs from a Path Decomposition Perspective for Preventing the Over-smoothing Jie Chen Weiqi Liu Zhizhong Huang Junbin Gao Junping Zhang Jian Pu 19 3 0 30 May 2022
SkipNode: On Alleviating Performance Degradation for Deep Graph Convolutional Networks Weigang Lu Yibing Zhan Binbin Lin Ziyu Guan Liu Liu Baosheng Yu Wei Zhao Yaming Yang Dacheng Tao GNN 13 13 0 22 Dec 2021
Graph Kernel Neural Networks Luca Cosmo G. Minello Alessandro Bicciato M. Bronstein Emanuele Rodolà Luca Rossi A. Torsello GNN 19 19 0 14 Dec 2021
AnchorGAE: General Data Clustering via $O(n)$ Bipartite Graph Convolution Hongyuan Zhang Jiankun Shi Rui Zhang Xuelong Li GNN 72 1 0 12 Nov 2021
Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective Wei Huang Yayong Li Weitao Du Jie Yin R. Xu Ling-Hao Chen Miao Zhang 22 17 0 03 Mar 2021
On the Proof of Global Convergence of Gradient Descent for Deep ReLU Networks with Linear Widths Quynh N. Nguyen 31 49 0 24 Jan 2021
Contextual Stochastic Block Models Y. Deshpande Andrea Montanari Elchanan Mossel S. Sen 98 151 0 23 Jul 2018