Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning

22 May 2018

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

50 / 62 papers shown

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 28 0 0 12 May 2025
Multi-Domain Causal Discovery in Bijective Causal Models Kasra Jalaldoust Saber Salehkaleybar Negar Kiyavash CML 64 0 0 30 Apr 2025
Robustness of Nonlinear Representation Learning Simon Buchholz Bernhard Schölkopf OOD 134 3 0 19 Mar 2025
I Predict Therefore I Am: Is Next Token Prediction Enough to Learn Human-Interpretable Concepts from Data? Yuhang Liu Dong Gong Erdun Gao Zhen Zhang Biwei Huang Mingming Gong Anton van den Hengel Javen Qinfeng Shi J. Shi 145 0 0 12 Mar 2025
All or None: Identifiable Linear Properties of Next-token Predictors in Language Modeling Emanuele Marconato Sébastien Lachapelle Sebastian Weichwald Luigi Gresele 66 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
Counterfactual Generative Modeling with Variational Causal Inference Yulun Wu Louie McConnell Claudia Iriondo CML BDL 24 0 0 16 Oct 2024
Analyzing (In)Abilities of SAEs via Formal Languages Abhinav Menon Manish Shrivastava David M. Krueger Ekdeep Singh Lubana 42 7 0 15 Oct 2024
Unsupervised Representation Learning from Sparse Transformation Analysis Yue Song Thomas Anderson Keller Yisong Yue Pietro Perona Max Welling DRL 29 0 0 07 Oct 2024
Learning Discrete Concepts in Latent Hierarchical Models Lingjing Kong Guan-Hong Chen Biwei Huang Eric P. Xing Yuejie Chi Kun Zhang 52 4 0 01 Jun 2024
Sparsity regularization via tree-structured environments for disentangled representations Elliot Layne Jason S. Hartford Sébastien Lachapelle Mathieu Blanchette Dhanya Sridhar OOD CML 28 0 0 30 May 2024
Separating common from salient patterns with Contrastive Representation Learning Robin Louiset Edouard Duchesnay Antoine Grigis Pietro Gori SSL DRL 38 1 0 19 Feb 2024
Beyond DAGs: A Latent Partial Causal Model for Multimodal Learning Yuhang Liu Zhen Zhang Dong Gong Biwei Huang Mingming Gong A. Hengel Kun Zhang Javen Qinfeng Shi J. Shi 41 7 0 09 Feb 2024
Towards Identifiable Unsupervised Domain Translation: A Diversified Distribution Matching Approach Sagar Shrestha Xiao Fu 23 3 0 18 Jan 2024
Step and Smooth Decompositions as Topological Clustering Luciano Vinas Arash A. Amini 14 0 0 09 Nov 2023
Identifying Semantic Component for Robust Molecular Property Prediction Zijian Li Zunhong Xu Ruichu Cai Zhenhui Yang Yuguang Yan Zhifeng Hao Guan-Hong Chen Kun Zhang 21 9 0 08 Nov 2023
Towards a Unified Framework of Contrastive Learning for Disentangled Representations Stefan Matthes Zhiwei Han Hao Shen 29 4 0 08 Nov 2023
Causal Representation Learning Made Identifiable by Grouping of Observational Variables H. Morioka Aapo Hyvarinen OOD CML BDL 30 9 0 24 Oct 2023
Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank Mouxiang Chen Chenghao Liu Zemin Liu Zhuo Li Jianling Sun CML 24 2 0 27 Sep 2023
Kernel Single Proxy Control for Deterministic Confounding Liyuan Xu A. Gretton CML 24 2 0 08 Aug 2023
Synaptic Plasticity Models and Bio-Inspired Unsupervised Deep Learning: A Survey Gabriele Lagani Fabrizio Falchi Claudio Gennaro Giuseppe Amato AAML 33 6 0 30 Jul 2023
Conditionally Invariant Representation Learning for Disentangling Cellular Heterogeneity H. Aliee Ferdinand Kapl Soroor Hediyeh-zadeh Fabian J. Theis CML 20 6 0 02 Jul 2023
Towards Characterizing Domain Counterfactuals For Invertible Latent Causal Models Zeyu Zhou Ruqi Bai Sean Kulinski Murat Kocaoglu David I. Inouye CML 24 1 0 20 Jun 2023
Partial Identifiability for Domain Adaptation Lingjing Kong Shaoan Xie Weiran Yao Yujia Zheng Guan-Hong Chen P. Stojanov Victor Akinwande Kun Zhang 45 8 0 10 Jun 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
Towards understanding neural collapse in supervised contrastive learning with the information bottleneck method Siwei Wang S. Palmer 16 2 0 19 May 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
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 50 11 0 29 Jan 2023
Linear Causal Disentanglement via Interventions C. Squires A. Seigal Salil Bhate Caroline Uhler CML 29 66 0 29 Nov 2022
Disentangled Representation Learning Xin Eric Wang Hong Chen Siao Tang Zihao Wu Wenwu Zhu DRL 32 77 0 21 Nov 2022
Temporally Disentangled Representation Learning Weiran Yao Guangyi Chen Kun Zhang CML BDL OOD 18 48 0 24 Oct 2022
Universal hidden monotonic trend estimation with contrastive learning Edouard Pineau S. Razakarivony Mauricio Gonzalez A. Schrapffer 23 0 0 18 Oct 2022
CLEAR: Generative Counterfactual Explanations on Graphs Jing Ma Ruocheng Guo Saumitra Mishra Aidong Zhang Jundong Li CML OOD 27 52 0 16 Oct 2022
Provable Subspace Identification Under Post-Nonlinear Mixtures Qi Lyu Xiao Fu CoGe 10 0 0 14 Oct 2022
Multi-View Independent Component Analysis with Shared and Individual Sources T. Pandeva Patrick Forré CML 13 5 0 05 Oct 2022
When are Post-hoc Conceptual Explanations Identifiable? Tobias Leemann Michael Kirchhof Yao Rong Enkelejda Kasneci Gjergji Kasneci 50 10 0 28 Jun 2022
Identifiability of deep generative models without auxiliary information Bohdan Kivva Goutham Rajendran Pradeep Ravikumar Bryon Aragam DRL 20 48 0 20 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
Learnable latent embeddings for joint behavioral and neural analysis Steffen Schneider Jin Hwa Lee Mackenzie W. Mathis 11 207 0 01 Apr 2022
From Statistical to Causal Learning Bernhard Schölkopf Julius von Kügelgen CML 28 45 0 01 Apr 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 15 0 0 14 Feb 2022
CITRIS: Causal Identifiability from Temporal Intervened Sequences Phillip Lippe Sara Magliacane Sindy Lowe Yuki M. Asano Taco S. Cohen E. Gavves CML 35 101 0 07 Feb 2022
Unsupervised Learning of Compositional Energy Concepts Yilun Du Shuang Li Yash Sharma J. Tenenbaum Igor Mordatch CoGe OCL 16 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
Towards Principled Causal Effect Estimation by Deep Identifiable Models Pengzhou (Abel) Wu Kenji Fukumizu BDL OOD CML 22 3 0 30 Sep 2021
Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal Effects Yao Zhang Jeroen Berrevoets M. Schaar CML 30 5 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 26 32 0 18 Jun 2021
Identifiability-Guaranteed Simplex-Structured Post-Nonlinear Mixture Learning via Autoencoder Qi Lyu Xiao Fu CML 17 12 0 16 Jun 2021
Contrastive Learning Inverts the Data Generating Process Roland S. Zimmermann Yash Sharma Steffen Schneider Matthias Bethge Wieland Brendel SSL 236 207 0 17 Feb 2021