Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks

7 December 2021

Papers citing "Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks"

35 / 35 papers shown

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
Tuning Algorithmic and Architectural Hyperparameters in Graph-Based Semi-Supervised Learning with Provable Guarantees Ally Yalei Du Eric Huang Dravyansh Sharma 39 0 0 18 Feb 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
Towards Graph Foundation Models: Learning Generalities Across Graphs via Task-Trees Zehong Wang Zheyuan Zhang Tianyi Ma Nitesh V. Chawla Chuxu Zhang Yanfang Ye AI4CE 71 0 0 21 Dec 2024
Optimal Exact Recovery in Semi-Supervised Learning: A Study of Spectral Methods and Graph Convolutional Networks Hai-Xiao Wang Zhichao Wang 66 1 0 18 Dec 2024
GFT: Graph Foundation Model with Transferable Tree Vocabulary Zehong Wang Zheyuan Zhang Nitesh V. Chawla Chuxu Zhang Yanfang Ye 31 9 0 09 Nov 2024
Towards Bridging Generalization and Expressivity of Graph Neural Networks Shouheng Li Floris Geerts Dongwoo Kim Qing Wang 18 0 0 14 Oct 2024
Deeper Insights into Deep Graph Convolutional Networks: Stability and Generalization Guangrui Yang Ming Li Han Feng Xiaosheng Zhuang GNN OOD BDL 21 2 0 11 Oct 2024
Generalization of Geometric Graph Neural Networks Zhiyang Wang J. Cerviño Alejandro Ribeiro 17 2 0 08 Sep 2024
Generalization of Graph Neural Networks is Robust to Model Mismatch Zhiyang Wang J. Cerviño Alejandro Ribeiro 32 1 0 25 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
A Manifold Perspective on the Statistical Generalization of Graph Neural Networks Zhiyang Wang J. Cerviño Alejandro Ribeiro AI4CE GNN 20 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 7 0 04 Jun 2024
Equivariant Machine Learning on Graphs with Nonlinear Spectral Filters Y. Lin Ronen Talmon Ron Levie 28 0 0 03 Jun 2024
PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning Jaejun Lee Minsung Hwang J. Whang 26 1 0 10 May 2024
Generalization of Graph Neural Networks through the Lens of Homomorphism Shouheng Li Dongwoo Kim Qing Wang 21 1 0 10 Mar 2024
On the Topology Awareness and Generalization Performance of Graph Neural Networks Junwei Su Chuan Wu AI4CE 24 0 0 07 Mar 2024
Weisfeiler-Leman at the margin: When more expressivity matters Billy J. Franks Christopher Morris A. Velingker Floris Geerts 42 9 0 12 Feb 2024
Generalization Error of Graph Neural Networks in the Mean-field Regime Gholamali Aminian Yixuan He G. Reinert Lukasz Szpruch Samuel N. Cohen 25 3 0 10 Feb 2024
PAC-Bayesian Adversarially Robust Generalization Bounds for Graph Neural Network Tan Sun Junhong Lin AAML 11 2 0 06 Feb 2024
Asymptotic generalization error of a single-layer graph convolutional network O. Duranthon L. Zdeborová MLT 35 2 0 06 Feb 2024
VC dimension of Graph Neural Networks with Pfaffian activation functions Giuseppe Alessio D’Inverno Monica Bianchini F. Scarselli GNN 8 1 0 22 Jan 2024
Information-Theoretic Generalization Bounds for Transductive Learning and its Applications Huayi Tang Yong Liu 39 1 0 08 Nov 2023
Sharp Generalization of Transductive Learning: A Transductive Local Rademacher Complexity Approach Yingzhen Yang 18 3 0 28 Sep 2023
A Model-Agnostic Graph Neural Network for Integrating Local and Global Information Wenzhuo Zhou Annie Qu Keiland W Cooper Norbert Fortin B. Shahbaba 17 1 0 23 Sep 2023
Approximately Equivariant Graph Networks Ningyuan Huang Ron Levie Soledad Villar 26 18 0 21 Aug 2023
Robust Graph Structure Learning with the Alignment of Features and Adjacency Matrix Shaogao Lv Gang Wen Shiyu Liu Linsen Wei Ming Li 23 3 0 05 Jul 2023
Towards Understanding the Generalization of Graph Neural Networks Huayi Tang Y. Liu GNN AI4CE 27 29 0 14 May 2023
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion Haotian Ju Dongyue Li Aneesh Sharma Hongyang R. Zhang 6 40 0 09 Feb 2023
WL meet VC Christopher Morris Floris Geerts Jan Tonshoff Martin Grohe 28 26 0 26 Jan 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 15 0 0 25 Jan 2023
Homophily modulates double descent generalization in graph convolution networks Chengzhi Shi Liming Pan Hong Hu Ivan Dokmanić 28 9 0 26 Dec 2022
TuneUp: A Simple Improved Training Strategy for Graph Neural Networks Weihua Hu Kaidi Cao Kexin Huang E-Wen Huang Karthik Subbian Kenji Kawaguchi J. Leskovec 19 0 0 26 Oct 2022
Analysis of Convolutions, Non-linearity and Depth in Graph Neural Networks using Neural Tangent Kernel Mahalakshmi Sabanayagam P. Esser D. Ghoshdastidar 13 2 0 18 Oct 2022
Out-Of-Distribution Generalization on Graphs: A Survey Haoyang Li Xin Eric Wang Ziwei Zhang Wenwu Zhu OOD CML 6 96 0 16 Feb 2022