The Incomplete Rosetta Stone Problem: Identifiability Results for Multi-View Nonlinear ICA

16 May 2019

Luigi Gresele

Paul Kishan Rubenstein

Arash Mehrjou

Francesco Locatello

Bernhard Schölkopf

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Papers citing "The Incomplete Rosetta Stone Problem: Identifiability Results for Multi-View Nonlinear ICA"

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Title
Causal View of Time Series Imputation: Some Identification Results on Missing Mechanism Ruichu Cai Kaitao Zheng Junxian Huang Zijian Li Zhengming Chen Boyan Xu Zhifeng Hao AI4TS CML 31 0 0 12 May 2025
Sanity Checking Causal Representation Learning on a Simple Real-World System Juan L. Gamella Simon Bing Jakob Runge CML 57 0 0 27 Feb 2025
Shortcuts and Identifiability in Concept-based Models from a Neuro-Symbolic Lens Samuele Bortolotti Emanuele Marconato Paolo Morettin Andrea Passerini Stefano Teso 61 2 0 16 Feb 2025
All or None: Identifiable Linear Properties of Next-token Predictors in Language Modeling Emanuele Marconato Sébastien Lachapelle Sebastian Weichwald Luigi Gresele 69 3 0 30 Oct 2024
Cross-Entropy Is All You Need To Invert the Data Generating Process Patrik Reizinger Alice Bizeul Attila Juhos Julia E. Vogt Randall Balestriero Wieland Brendel David Klindt SSL OOD BDL DRL 102 3 0 29 Oct 2024
InfoNCE: Identifying the Gap Between Theory and Practice E. Rusak Patrik Reizinger Attila Juhos Oliver Bringmann Roland S. Zimmermann Wieland Brendel 33 5 0 28 Jun 2024
Sparsity regularization via tree-structured environments for disentangled representations Elliot Layne Jason S. Hartford Sébastien Lachapelle Mathieu Blanchette Dhanya Sridhar OOD CML 33 0 0 30 May 2024
Beyond DAGs: A Latent Partial Causal Model for Multimodal Learning Yuhang Liu Zhen Zhang Dong Gong Biwei Huang Biwei Huang A. Hengel Kun Zhang Anton van den Hengel Javen Qinfeng Shi 46 7 0 09 Feb 2024
Towards a Unified Framework of Contrastive Learning for Disentangled Representations Stefan Matthes Zhiwei Han Hao Shen 31 4 0 08 Nov 2023
Causal Representation Learning Made Identifiable by Grouping of Observational Variables H. Morioka Aapo Hyvarinen OOD CML BDL 33 9 0 24 Oct 2023
Conditionally Invariant Representation Learning for Disentangling Cellular Heterogeneity H. Aliee Ferdinand Kapl Soroor Hediyeh-zadeh Fabian J. Theis CML 23 6 0 02 Jul 2023
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 18 56 0 01 Jun 2023
Identifiability of latent-variable and structural-equation models: from linear to nonlinear Aapo Hyvarinen Ilyes Khemakhem R. Monti CML 30 41 0 06 Feb 2023
Provable Subspace Identification Under Post-Nonlinear Mixtures Qi Lyu Xiao Fu CoGe 23 0 0 14 Oct 2022
Multi-View Independent Component Analysis with Shared and Individual Sources T. Pandeva Patrick Forré CML 15 5 0 05 Oct 2022
Embrace the Gap: VAEs Perform Independent Mechanism Analysis Patrik Reizinger Luigi Gresele Jack Brady Julius von Kügelgen Dominik Zietlow Bernhard Schölkopf Georg Martius Wieland Brendel M. Besserve DRL 35 19 0 06 Jun 2022
Weakly Supervised Representation Learning with Sparse Perturbations Kartik Ahuja Jason S. Hartford Yoshua Bengio SSL 35 58 0 02 Jun 2022
On Pitfalls of Identifiability in Unsupervised Learning. A Note on: "Desiderata for Representation Learning: A Causal Perspective" Shubhangi Ghosh Luigi Gresele Julius von Kügelgen M. Besserve Bernhard Schölkopf CML 17 0 0 14 Feb 2022
Contrastively Disentangled Sequential Variational Autoencoder M. Kiener Weiran Wang Michael Gerndt CoGe DRL 24 40 0 22 Oct 2021
Identifiability-Guaranteed Simplex-Structured Post-Nonlinear Mixture Learning via Autoencoder Qi Lyu Xiao Fu CML 25 12 0 16 Jun 2021
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
A Commentary on the Unsupervised Learning of Disentangled Representations Francesco Locatello Stefan Bauer Mario Lucic Gunnar Rätsch Sylvain Gelly Bernhard Schölkopf Olivier Bachem OOD DRL 24 20 0 28 Jul 2020
Relative gradient optimization of the Jacobian term in unsupervised deep learning Luigi Gresele G. Fissore Adrián Javaloy Bernhard Schölkopf Aapo Hyvarinen DRL 16 22 0 26 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
Weakly-Supervised Disentanglement Without Compromises Francesco Locatello Ben Poole Gunnar Rätsch Bernhard Schölkopf Olivier Bachem Michael Tschannen CoGe OOD DRL 184 313 0 07 Feb 2020
Leveraging directed causal discovery to detect latent common causes Ciarán M. Gilligan-Lee Chris Hart Jonathan G. Richens Saurabh Johri CML 21 16 0 22 Oct 2019
Weakly Supervised Disentanglement with Guarantees Rui Shu Yining Chen Abhishek Kumar Stefano Ermon Ben Poole CoGe DRL 28 136 0 22 Oct 2019
Disentangling Factors of Variation Using Few Labels Francesco Locatello Michael Tschannen Stefan Bauer Gunnar Rätsch Bernhard Schölkopf Olivier Bachem DRL CML CoGe 11 122 0 03 May 2019