Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding

21 July 2020

Wieland Brendel

Papers citing "Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding"

43 / 93 papers shown

Title
Emerging Synergies in Causality and Deep Generative Models: A Survey Guanglin Zhou Shaoan Xie Guang-Yuan Hao Shiming Chen Biwei Huang Xiwei Xu Chen Wang Liming Zhu Lina Yao Kun Zhang AI4CE 53 11 0 29 Jan 2023
Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning Yuejiang Liu Alexandre Alahi Chris Russell Max Horn Dominik Zietlow Bernhard Schölkopf Francesco Locatello CML 56 22 0 12 Jan 2023
Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning Sébastien Lachapelle T. Deleu Divyat Mahajan Ioannis Mitliagkas Yoshua Bengio Simon Lacoste-Julien Quentin Bertrand 18 32 0 26 Nov 2022
Mechanistic Mode Connectivity Ekdeep Singh Lubana Eric J. Bigelow Robert P. Dick David M. Krueger Hidenori Tanaka 27 45 0 15 Nov 2022
Temporally Disentangled Representation Learning Weiran Yao Guangyi Chen Kun Zhang CML BDL OOD 21 48 0 24 Oct 2022
Disentanglement of Correlated Factors via Hausdorff Factorized Support Karsten Roth Mark Ibrahim Zeynep Akata Pascal Vincent Diane Bouchacourt CML OOD CoGe 33 33 0 13 Oct 2022
Unsupervised Learning of Equivariant Structure from Sequences Takeru Miyato Masanori Koyama Kenji Fukumizu 13 12 0 12 Oct 2022
Understanding Neural Coding on Latent Manifolds by Sharing Features and Dividing Ensembles Martin Bjerke Lukas Schott Kristopher T. Jensen Claudia Battistin David A. Klindt Benjamin A. Dunn 22 7 0 06 Oct 2022
A Multiagent Framework for the Asynchronous and Collaborative Extension of Multitask ML Systems Andrea Gesmundo 21 2 0 29 Sep 2022
Interventional Causal Representation Learning Kartik Ahuja Divyat Mahajan Yixin Wang Yoshua Bengio CML 39 83 0 24 Sep 2022
A Continual Development Methodology for Large-scale Multitask Dynamic ML Systems Andrea Gesmundo 19 18 0 15 Sep 2022
Pixel-level Correspondence for Self-Supervised Learning from Video Yash Sharma Yi Zhu Chris Russell Thomas Brox SSL 8 4 0 08 Jul 2022
Identifiability of deep generative models without auxiliary information Bohdan Kivva Goutham Rajendran Pradeep Ravikumar Bryon Aragam DRL 23 48 0 20 Jun 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 24 28 0 13 Jun 2022
An Empirical Study on Disentanglement of Negative-free Contrastive Learning Jinkun Cao Ruiqian Nai Qing Yang Jialei Huang Yang Gao CoGe DRL 19 9 0 09 Jun 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 30 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
Indeterminacy in Generative Models: Characterization and Strong Identifiability Quanhan Xi Benjamin Bloem-Reddy 6 22 0 02 Jun 2022
An Evolutionary Approach to Dynamic Introduction of Tasks in Large-scale Multitask Learning Systems Andrea Gesmundo J. Dean 31 23 0 25 May 2022
Lost in Latent Space: Disentangled Models and the Challenge of Combinatorial Generalisation M. Montero J. Bowers Rui Ponte Costa Casimir J. H. Ludwig Gaurav Malhotra DRL CoGe 17 11 0 05 Apr 2022
Learnable latent embeddings for joint behavioral and neural analysis Steffen Schneider Jin Hwa Lee Mackenzie W. Mathis 11 207 0 01 Apr 2022
Learning Latent Causal Dynamics Weiran Yao Guan-Hong Chen Kun Zhang OOD CML OffRL 14 13 0 10 Feb 2022
CITRIS: Causal Identifiability from Temporal Intervened Sequences Phillip Lippe Sara Magliacane Sindy Lowe Yuki M. Asano Taco S. Cohen E. Gavves CML 40 101 0 07 Feb 2022
Disentanglement and Generalization Under Correlation Shifts Christina M. Funke Paul Vicol Kuan-Chieh Jackson Wang Matthias Kümmerer R. Zemel Matthias Bethge OOD 31 7 0 29 Dec 2021
Object Pursuit: Building a Space of Objects via Discriminative Weight Generation Chuanyu Pan Yanchao Yang Kaichun Mo Yueqi Duan Leonidas J. Guibas OCL 21 1 0 15 Dec 2021
Unsupervised Learning of Compositional Energy Concepts Yilun Du Shuang Li Yash Sharma J. Tenenbaum Igor Mordatch CoGe OCL 19 76 0 04 Nov 2021
Properties from Mechanisms: An Equivariance Perspective on Identifiable Representation Learning Kartik Ahuja Jason S. Hartford Yoshua Bengio 21 38 0 29 Oct 2021
Learning Temporally Causal Latent Processes from General Temporal Data Weiran Yao Yuewen Sun Alex Ho Changyin Sun Kun Zhang BDL CML 14 85 0 11 Oct 2021
Topographic VAEs learn Equivariant Capsules Thomas Anderson Keller Max Welling BDL 36 38 0 03 Sep 2021
Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA Sébastien Lachapelle Pau Rodríguez López Yash Sharma Katie Everett Rémi Le Priol Alexandre Lacoste Simon Lacoste-Julien CML OOD 41 133 0 21 Jul 2021
Visual Representation Learning Does Not Generalize Strongly Within the Same Domain Lukas Schott Julius von Kügelgen Frederik Trauble Peter V. Gehler Chris Russell Matthias Bethge Bernhard Schölkopf Francesco Locatello Wieland Brendel OOD DRL 35 66 0 17 Jul 2021
An Image is Worth More Than a Thousand Words: Towards Disentanglement in the Wild Aviv Gabbay Niv Cohen Yedid Hoshen CoGe DRL 23 33 0 29 Jun 2021
Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA Hermanni Hälvä Sylvain Le Corff Luc Lehéricy Jonathan So Yongjie Zhu Elisabeth Gassiat Aapo Hyvarinen CML 29 64 0 17 Jun 2021
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style Julius von Kügelgen Yash Sharma Luigi Gresele Wieland Brendel Bernhard Schölkopf M. Besserve Francesco Locatello 17 302 0 08 Jun 2021
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization Damien Teney Ehsan Abbasnejad Simon Lucey A. Hengel 23 86 0 12 May 2021
Variable-rate discrete representation learning Sander Dieleman C. Nash Jesse Engel Karen Simonyan BDL DRL 24 23 0 10 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
Demystifying Inductive Biases for $β$ -VAE Based Architectures Dominik Zietlow Michal Rolínek Georg Martius CoGe DRL CML 11 8 0 12 Feb 2021
Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement A. Ross Finale Doshi-Velez DRL 14 13 0 09 Feb 2021
Autoencoding Slow Representations for Semi-supervised Data Efficient Regression Oliver Struckmeier Kshitij Tiwari Ville Kyrki DRL 23 3 0 11 Dec 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 27 80 0 27 Oct 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 26 115 0 14 Jun 2020
Weakly-Supervised Disentanglement Without Compromises Francesco Locatello Ben Poole Gunnar Rätsch Bernhard Schölkopf Olivier Bachem Michael Tschannen CoGe OOD DRL 178 313 0 07 Feb 2020