Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning

22 May 2018

Papers citing "Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning"

33 / 83 papers shown

Title
Unsupervised Learning of Compositional Energy Concepts Yilun Du Shuang Li Yash Sharma J. Tenenbaum Igor Mordatch CoGe OCL 30 76 0 04 Nov 2021
Properties from Mechanisms: An Equivariance Perspective on Identifiable Representation Learning Kartik Ahuja Jason S. Hartford Yoshua Bengio 34 38 0 29 Oct 2021
Discovery of Single Independent Latent Variable Uri Shaham Jonathan Svirsky Ori Katz Ronen Talmon CML 28 2 0 12 Oct 2021
Learning Temporally Causal Latent Processes from General Temporal Data Weiran Yao Yuewen Sun Alex Ho Changyin Sun Kun Zhang BDL CML 35 85 0 11 Oct 2021
Towards Principled Causal Effect Estimation by Deep Identifiable Models Pengzhou (Abel) Wu Kenji Fukumizu BDL OOD CML 30 3 0 30 Sep 2021
Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal Effects Yao Zhang Jeroen Berrevoets M. Schaar CML 36 6 0 06 Aug 2021
Iterative Feature Matching: Toward Provable Domain Generalization with Logarithmic Environments Yining Chen Elan Rosenfeld Mark Sellke Tengyu Ma Andrej Risteski OOD 36 33 0 18 Jun 2021
Identifiability-Guaranteed Simplex-Structured Post-Nonlinear Mixture Learning via Autoencoder Qi Lyu Xiao Fu CML 33 12 0 16 Jun 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
Learning disentangled representations via product manifold projection Marco Fumero Luca Cosmo Simone Melzi Emanuele Rodolà CoGe DRL 23 22 0 02 Mar 2021
Contrastive Learning Inverts the Data Generating Process Roland S. Zimmermann Yash Sharma Steffen Schneider Matthias Bethge Wieland Brendel SSL 238 211 0 17 Feb 2021
Causal Autoregressive Flows Ilyes Khemakhem R. Monti R. Leech Aapo Hyvarinen CML OOD AI4CE 27 108 0 04 Nov 2020
Latent Causal Invariant Model Xinwei Sun Botong Wu Xiangyu Zheng Chang-Shu Liu Wei Chen Tao Qin Tie-Yan Liu OOD CML BDL 31 14 0 04 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 35 80 0 27 Oct 2020
A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation Francesco Locatello Stefan Bauer Mario Lucic Gunnar Rätsch Sylvain Gelly Bernhard Schölkopf Olivier Bachem OOD 14 66 0 27 Oct 2020
Contrastive learning, multi-view redundancy, and linear models Christopher Tosh A. Krishnamurthy Daniel J. Hsu SSL 35 163 0 24 Aug 2020
Uncovering the structure of clinical EEG signals with self-supervised learning Hubert J. Banville O. Chehab Aapo Hyvarinen D. Engemann Alexandre Gramfort 36 195 0 31 Jul 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 48 132 0 21 Jul 2020
Time Series Source Separation with Slow Flows Edouard Pineau S. Razakarivony Thomas Bonald BDL AI4TS 47 2 0 20 Jul 2020
Relative gradient optimization of the Jacobian term in unsupervised deep learning Luigi Gresele G. Fissore Adrián Javaloy Bernhard Schölkopf Aapo Hyvarinen DRL 19 22 0 26 Jun 2020
Independent Innovation Analysis for Nonlinear Vector Autoregressive Process H. Morioka Hermanni Hälvä Aapo Hyvarinen 25 22 0 19 Jun 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
A theory of independent mechanisms for extrapolation in generative models M. Besserve Rémy Sun Dominik Janzing Bernhard Schölkopf 22 25 0 01 Apr 2020
Few-shot Domain Adaptation by Causal Mechanism Transfer Takeshi Teshima Issei Sato Masashi Sugiyama OOD CML TTA 33 86 0 10 Feb 2020
Weakly-Supervised Disentanglement Without Compromises Francesco Locatello Ben Poole Gunnar Rätsch Bernhard Schölkopf Olivier Bachem Michael Tschannen CoGe OOD DRL 184 314 0 07 Feb 2020
Causal Mosaic: Cause-Effect Inference via Nonlinear ICA and Ensemble Method Pengzhou (Abel) Wu Kenji Fukumizu CML 27 26 0 07 Jan 2020
Supervise Thyself: Examining Self-Supervised Representations in Interactive Environments Evan Racah C. Pal SSL 27 2 0 27 Jun 2019
Explicit Disentanglement of Appearance and Perspective in Generative Models N. Detlefsen Søren Hauberg CoGe DRL 30 47 0 11 Jun 2019
Putting An End to End-to-End: Gradient-Isolated Learning of Representations Sindy Löwe Peter O'Connor Bastiaan S. Veeling SSL 14 143 0 28 May 2019
Disentangling Factors of Variation Using Few Labels Francesco Locatello Michael Tschannen Stefan Bauer Gunnar Rätsch Bernhard Schölkopf Olivier Bachem DRL CML CoGe 34 123 0 03 May 2019
Time Series Source Separation using Dynamic Mode Decomposition Arvind Prasadan R. Nadakuditi AI4TS 21 6 0 04 Mar 2019
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms Yoshua Bengio T. Deleu Nasim Rahaman Nan Rosemary Ke Sébastien Lachapelle O. Bilaniuk Anirudh Goyal C. Pal CML OOD 48 332 0 30 Jan 2019
Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness Raphael Suter Ðorðe Miladinovic Bernhard Schölkopf Stefan Bauer CML OOD DRL 21 159 0 31 Oct 2018