A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks

14 December 2020

Papers citing "A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks"

20 / 20 papers shown

Title
Information-Theoretic Generalization Bounds for Transductive Learning and its Applications Huayi Tang Yong Liu 57 1 0 08 Nov 2023
Sharpness-Aware Graph Collaborative Filtering Huiyuan Chen Chin-Chia Michael Yeh Yujie Fan Yan Zheng Junpeng Wang Vivian Lai Mahashweta Das Hao Yang 26 5 0 18 Jul 2023
A graphon-signal analysis of graph neural networks Ron Levie 26 17 0 25 May 2023
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion Haotian Ju Dongyue Li Aneesh Sharma Hongyang R. Zhang 23 40 0 09 Feb 2023
Adversarial Weight Perturbation Improves Generalization in Graph Neural Networks Yihan Wu Aleksandar Bojchevski Heng Huang AAML 34 30 0 09 Dec 2022
Provably expressive temporal graph networks Amauri Souza Diego Mesquita Samuel Kaski Vikas K. Garg 89 54 0 29 Sep 2022
Theory of Graph Neural Networks: Representation and Learning Stefanie Jegelka GNN AI4CE 33 68 0 16 Apr 2022
Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning Wei Huang Chunrui Liu Yilan Chen Tianyu Liu R. Xu BDL MLT 19 2 0 04 Feb 2022
Debiased Graph Neural Networks with Agnostic Label Selection Bias Shaohua Fan Xiao Wang Chuan Shi Kun Kuang Nian Liu Bai Wang AI4CE 36 38 0 19 Jan 2022
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks P. Esser L. C. Vankadara D. Ghoshdastidar 28 53 0 07 Dec 2021
Multi-fidelity Stability for Graph Representation Learning Yihan He Joan Bruna 17 0 0 25 Nov 2021
Generalizing Graph Neural Networks on Out-Of-Distribution Graphs Shaohua Fan Xiao Wang Chuan Shi Peng Cui Bai Wang CML OOD OODD AI4CE 49 81 0 20 Nov 2021
Learning on Random Balls is Sufficient for Estimating (Some) Graph Parameters Takanori Maehara Hoang NT 35 2 0 05 Nov 2021
On Provable Benefits of Depth in Training Graph Convolutional Networks Weilin Cong M. Ramezani M. Mahdavi 21 73 0 28 Oct 2021
Reconstruction for Powerful Graph Representations Leonardo Cotta Christopher Morris Bruno Ribeiro AI4CE 127 78 0 01 Oct 2021
Layer-wise Adaptive Graph Convolution Networks Using Generalized Pagerank Kishan Wimalawarne Taiji Suzuki GNN 19 2 0 24 Aug 2021
From Local Structures to Size Generalization in Graph Neural Networks Gilad Yehudai Ethan Fetaya E. Meirom Gal Chechik Haggai Maron GNN AI4CE 162 123 0 17 Oct 2020
Spatially-Aware Graph Neural Networks for Relational Behavior Forecasting from Sensor Data Sergio Casas Cole Gulino Renjie Liao R. Urtasun AI4CE 174 211 0 18 Oct 2019
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 251 1,811 0 25 Nov 2016
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 250 3,236 0 24 Nov 2016