Neural Networks for Learning Counterfactual G-Invariances from Single Environments

20 April 2021

Papers citing "Neural Networks for Learning Counterfactual G-Invariances from Single Environments"

6 / 6 papers shown

Title
A tradeoff between universality of equivariant models and learnability of symmetries Vasco Portilheiro 35 2 0 17 Oct 2022
OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs Yangze Zhou Gitta Kutyniok Bruno Ribeiro OODD AI4CE 81 37 0 30 May 2022
Size-Invariant Graph Representations for Graph Classification Extrapolations Beatrice Bevilacqua Yangze Zhou Bruno Ribeiro OOD 35 108 0 08 Mar 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 215 901 0 02 Mar 2020
A General Theory of Equivariant CNNs on Homogeneous Spaces Taco S. Cohen Mario Geiger Maurice Weiler MLT AI4CE 165 308 0 05 Nov 2018
Learning Representations for Counterfactual Inference Fredrik D. Johansson Uri Shalit David Sontag CML OOD BDL 232 719 0 12 May 2016