Generalizing Graph Neural Networks on Out-Of-Distribution Graphs

Generalizing Graph Neural Networks on Out-Of-Distribution Graphs

20 November 2021

Peng Cui

Papers citing "Generalizing Graph Neural Networks on Out-Of-Distribution Graphs"

7 / 57 papers shown

Title
Discovering Invariant Rationales for Graph Neural Networks Yingmin Wu Xiang Wang An Zhang Xiangnan He Tat-Seng Chua OOD AI4CE 89 222 0 30 Jan 2022
Does Invariant Risk Minimization Capture Invariance? Pritish Kamath Akilesh Tangella Danica J. Sutherland Nathan Srebro OOD 185 125 0 04 Jan 2021
Beyond Low-frequency Information in Graph Convolutional Networks Deyu Bo Xiao Wang C. Shi Huawei Shen GNN 87 554 0 04 Jan 2021
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 215 898 0 02 Mar 2020
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 229 1,935 0 09 Jun 2018
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 159 1,766 0 02 Mar 2017
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 234 1,809 0 25 Nov 2016