Group invariance principles for causal generative models

Group invariance principles for causal generative models

5 May 2017

Naji Shajarisales

Bernhard Schölkopf

Dominik Janzing

Papers citing "Group invariance principles for causal generative models"

10 / 10 papers shown

Title
Nonparametric Identifiability of Causal Representations from Unknown Interventions Julius von Kügelgen M. Besserve Wendong Liang Luigi Gresele Armin Kekić Elias Bareinboim David M. Blei Bernhard Schölkopf CML 38 57 0 01 Jun 2023
Mechanistic Mode Connectivity Ekdeep Singh Lubana Eric J. Bigelow Robert P. Dick David M. Krueger Hidenori Tanaka 34 45 0 15 Nov 2022
From Statistical to Causal Learning Bernhard Schölkopf Julius von Kügelgen CML 34 45 0 01 Apr 2022
Learning soft interventions in complex equilibrium systems M. Besserve Bernhard Schölkopf 29 3 0 10 Dec 2021
Independent mechanism analysis, a new concept? Luigi Gresele Julius von Kügelgen Vincent Stimper Bernhard Schölkopf M. Besserve CML 23 100 0 09 Jun 2021
Size-Invariant Graph Representations for Graph Classification Extrapolations Beatrice Bevilacqua Yangze Zhou Bruno Ribeiro OOD 42 108 0 08 Mar 2021
Counterfactual Zero-Shot and Open-Set Visual Recognition Zhongqi Yue Tan Wang Hanwang Zhang Qianru Sun Xiansheng Hua BDL 166 194 0 01 Mar 2021
Learning Causal Semantic Representation for Out-of-Distribution Prediction Chang-Shu Liu Xinwei Sun Jindong Wang Haoyue Tang Tao Li Tao Qin Wei Chen Tie-Yan Liu CML OODD OOD 35 104 0 03 Nov 2020
A theory of independent mechanisms for extrapolation in generative models M. Besserve Rémy Sun Dominik Janzing Bernhard Schölkopf 28 25 0 01 Apr 2020
Counterfactuals uncover the modular structure of deep generative models M. Besserve Arash Mehrjou Rémy Sun Bernhard Schölkopf DRL BDL DiffM 19 107 0 08 Dec 2018