Weakly-Supervised Disentanglement Without Compromises

7 February 2020

Francesco Locatello

Olivier Bachem

Papers citing "Weakly-Supervised Disentanglement Without Compromises"

20 / 70 papers shown

Title
Disentanglement and Generalization Under Correlation Shifts Christina M. Funke Paul Vicol Kuan-Chieh Jackson Wang Matthias Kümmerer R. Zemel Matthias Bethge OOD 36 7 0 29 Dec 2021
On Causally Disentangled Representations Abbavaram Gowtham Reddy Benin Godfrey L V. Balasubramanian OOD CML 34 21 0 10 Dec 2021
Unsupervised Learning of Compositional Energy Concepts Yilun Du Shuang Li Yash Sharma J. Tenenbaum Igor Mordatch CoGe OCL 21 76 0 04 Nov 2021
Properties from Mechanisms: An Equivariance Perspective on Identifiable Representation Learning Kartik Ahuja Jason S. Hartford Yoshua Bengio 26 38 0 29 Oct 2021
SpectroscopyNet: Learning to pre-process Spectroscopy Signals without clean data Juan Castorena Diane Oyen 16 0 0 26 Oct 2021
Group-disentangled Representation Learning with Weakly-Supervised Regularization Linh-Tam Tran Amir Hosein Khasahmadi Aditya Sanghi Saeid Asgari Taghanaki DRL 34 1 0 23 Oct 2021
Contrastively Disentangled Sequential Variational Autoencoder M. Kiener Weiran Wang Michael Gerndt CoGe DRL 24 40 0 22 Oct 2021
Identifiable Deep Generative Models via Sparse Decoding Gemma E. Moran Dhanya Sridhar Yixin Wang David M. Blei BDL 28 44 0 20 Oct 2021
Be More Active! Understanding the Differences between Mean and Sampled Representations of Variational Autoencoders Lisa Bonheme M. Grzes DRL 13 6 0 26 Sep 2021
Desiderata for Representation Learning: A Causal Perspective Yixin Wang Michael I. Jordan CML 32 80 0 08 Sep 2021
Counterfactual Invariance to Spurious Correlations: Why and How to Pass Stress Tests Victor Veitch Alexander DÁmour Steve Yadlowsky Jacob Eisenstein OOD 16 91 0 31 May 2021
Where and What? Examining Interpretable Disentangled Representations Xinqi Zhu Chang Xu Dacheng Tao FAtt DRL 48 38 0 07 Apr 2021
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations Pau Rodríguez López Massimo Caccia Alexandre Lacoste L. Zamparo I. Laradji Laurent Charlin David Vazquez AAML 34 55 0 18 Mar 2021
Contrastive Learning Inverts the Data Generating Process Roland S. Zimmermann Yash Sharma Steffen Schneider Matthias Bethge Wieland Brendel SSL 238 207 0 17 Feb 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 32 104 0 03 Nov 2020
On the Transfer of Disentangled Representations in Realistic Settings Andrea Dittadi Frederik Trauble Francesco Locatello M. Wuthrich Vaibhav Agrawal Ole Winther Stefan Bauer Bernhard Schölkopf OOD 33 80 0 27 Oct 2020
Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning S. Sontakke Arash Mehrjou Laurent Itti Bernhard Schölkopf CML 17 60 0 07 Oct 2020
Deep Anomaly Detection by Residual Adaptation Lucas Deecke Lukas Ruff Robert A. Vandermeulen Hakan Bilen UQCV 23 4 0 05 Oct 2020
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding David A. Klindt Lukas Schott Yash Sharma Ivan Ustyuzhaninov Wieland Brendel Matthias Bethge Dylan M. Paiton CML 45 132 0 21 Jul 2020
On Disentangled Representations Learned From Correlated Data Frederik Trauble Elliot Creager Niki Kilbertus Francesco Locatello Andrea Dittadi Anirudh Goyal Bernhard Schölkopf Stefan Bauer OOD CML 29 115 0 14 Jun 2020