Embrace the Gap: VAEs Perform Independent Mechanism Analysis

Embrace the Gap: VAEs Perform Independent Mechanism Analysis

6 June 2022

Patrik Reizinger

Julius von Kügelgen

Dominik Zietlow

Bernhard Schölkopf

Wieland Brendel

Papers citing "Embrace the Gap: VAEs Perform Independent Mechanism Analysis"

18 / 18 papers shown

Title
An Empirically Grounded Identifiability Theory Will Accelerate Self-Supervised Learning Research Patrik Reizinger Randall Balestriero David Klindt Wieland Brendel 36 0 0 17 Apr 2025
Robustness of Nonlinear Representation Learning Simon Buchholz Bernhard Schölkopf OOD 59 3 0 19 Mar 2025
Unpicking Data at the Seams: Understanding Disentanglement in VAEs Carl Allen CML CoGe 25 0 0 29 Oct 2024
Analyzing Generative Models by Manifold Entropic Metrics Daniel Galperin Ullrich Köthe DRL 16 0 0 25 Oct 2024
Causal Representation Learning in Temporal Data via Single-Parent Decoding Philippe Brouillard Sébastien Lachapelle Julia Kaltenborn Yaniv Gurwicz Dhanya Sridhar Alexandre Drouin Peer Nowack Jakob Runge David Rolnick CML 22 3 0 09 Oct 2024
Bayesian Intrinsic Groupwise Image Registration: Unsupervised Disentanglement of Anatomy and Geometry Xinzhe Luo Xin Wang Linda Shapiro Chun Yuan Jianfeng Feng Xiahai Zhuang 12 0 0 04 Jan 2024
From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling Aneesh Komanduri Xintao Wu Yongkai Wu Feng Chen CML OOD 23 7 0 17 Oct 2023
Deep Backtracking Counterfactuals for Causally Compliant Explanations Klaus-Rudolf Kladny Julius von Kügelgen Bernhard Schölkopf Michael Muehlebach BDL 24 4 0 11 Oct 2023
Compositional Generalization from First Principles Thaddäus Wiedemer Prasanna Mayilvahanan Matthias Bethge Wieland Brendel OCL 22 36 0 10 Jul 2023
Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation Sébastien Lachapelle Divyat Mahajan Ioannis Mitliagkas Simon Lacoste-Julien 21 25 0 05 Jul 2023
High Fidelity Image Counterfactuals with Probabilistic Causal Models Fabio De Sousa Ribeiro Tian Xia M. Monteiro Nick Pawlowski Ben Glocker DiffM 20 35 0 27 Jun 2023
BISCUIT: Causal Representation Learning from Binary Interactions Phillip Lippe Sara Magliacane Sindy Lowe Yuki M. Asano Taco S. Cohen E. Gavves CML 31 28 0 16 Jun 2023
Provably Learning Object-Centric Representations Jack Brady Roland S. Zimmermann Yash Sharma Bernhard Schölkopf Julius von Kügelgen Wieland Brendel OCL 26 31 0 23 May 2023
Function Classes for Identifiable Nonlinear Independent Component Analysis Simon Buchholz M. Besserve Bernhard Schölkopf 11 36 0 12 Aug 2022
Causal Representation Learning for Instantaneous and Temporal Effects in Interactive Systems Phillip Lippe Sara Magliacane Sindy Lowe Yuki M. Asano Taco S. Cohen E. Gavves CML 19 28 0 13 Jun 2022
Be More Active! Understanding the Differences between Mean and Sampled Representations of Variational Autoencoders Lisa Bonheme M. Grzes DRL 4 6 0 26 Sep 2021
Contrastive Learning Inverts the Data Generating Process Roland S. Zimmermann Yash Sharma Steffen Schneider Matthias Bethge Wieland Brendel SSL 236 206 0 17 Feb 2021
Weakly-Supervised Disentanglement Without Compromises Francesco Locatello Ben Poole Gunnar Rätsch Bernhard Schölkopf Olivier Bachem Michael Tschannen CoGe OOD DRL 171 311 0 07 Feb 2020