Linear Causal Disentanglement via Interventions

29 November 2022

Papers citing "Linear Causal Disentanglement via Interventions"

48 / 48 papers shown

Title
Robustness of Nonlinear Representation Learning Simon Buchholz Bernhard Schölkopf OOD 131 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 142 0 0 12 Mar 2025
Sanity Checking Causal Representation Learning on a Simple Real-World System Juan L. Gamella Simon Bing Jakob Runge CML 50 0 0 27 Feb 2025
Identifying General Mechanism Shifts in Linear Causal Representations Tianyu Chen Kevin Bello Francesco Locatello Bryon Aragam Pradeep Ravikumar OOD CML 33 3 0 31 Oct 2024
Identifiability Guarantees for Causal Disentanglement from Purely Observational Data Ryan Welch Jiaqi Zhang Caroline Uhler CML OOD 51 1 0 31 Oct 2024
Identifiability Analysis of Linear ODE Systems with Hidden Confounders Yuanyuan Wang Biwei Huang Wei Huang Xi Geng Mingming Gong CML 28 0 0 29 Oct 2024
Language Agents Meet Causality -- Bridging LLMs and Causal World Models John Gkountouras Matthias Lindemann Phillip Lippe E. Gavves Ivan Titov LRM 28 0 0 25 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
Automated Discovery of Pairwise Interactions from Unstructured Data Zuheng Xu Moksh Jain Ali Denton Shawn Whitfield Aniket Didolkar Berton A. Earnshaw Jason S. Hartford 23 2 0 11 Sep 2024
Linear causal disentanglement via higher-order cumulants Paula Leyes Carreno Chiara Meroni A. Seigal CML 34 0 0 05 Jul 2024
Linear Causal Representation Learning from Unknown Multi-node Interventions Burak Varıcı Emre Acartürk Karthikeyan Shanmugam A. Tajer CML 29 1 0 09 Jun 2024
Smoke and Mirrors in Causal Downstream Tasks Riccardo Cadei Lukas Lindorfer Sylvia Cremer Cordelia Schmid Francesco Locatello CML 28 3 0 27 May 2024
Learning Invariant Causal Mechanism from Vision-Language Models Zeen Song Siyu Zhao Xingyu Zhang Jiangmeng Li Changwen Zheng Wenwen Qiang CML BDL VLM 35 0 0 24 May 2024
Marrying Causal Representation Learning with Dynamical Systems for Science Dingling Yao Caroline Muller Francesco Locatello CML AI4CE 40 6 0 22 May 2024
Propensity Score Alignment of Unpaired Multimodal Data Johnny Xi Jason S. Hartford 24 2 0 02 Apr 2024
Identifiable Latent Neural Causal Models Yuhang Liu Zhen Zhang Dong Gong Mingming Gong Biwei Huang A. Hengel Kun Zhang Javen Qinfeng Shi CML OOD 32 7 0 23 Mar 2024
A Sparsity Principle for Partially Observable Causal Representation Learning Danru Xu Dingling Yao Sébastien Lachapelle Perouz Taslakian Julius von Kügelgen Francesco Locatello Sara Magliacane CML 34 13 0 13 Mar 2024
Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models Goutham Rajendran Simon Buchholz Bryon Aragam Bernhard Schölkopf Pradeep Ravikumar AI4CE 88 21 0 14 Feb 2024
Causal Representation Learning from Multiple Distributions: A General Setting Kun Zhang Shaoan Xie Ignavier Ng Yujia Zheng CML OOD 29 18 0 07 Feb 2024
Invariance & Causal Representation Learning: Prospects and Limitations Simon Bing Jonas Wahl Urmi Ninad Jakob Runge CML OOD 38 3 0 06 Dec 2023
Targeted Reduction of Causal Models Armin Kekić Bernhard Schölkopf M. Besserve CML 50 9 0 30 Nov 2023
Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations Cian Eastwood Julius von Kügelgen Linus Ericsson Diane Bouchacourt Pascal Vincent Bernhard Schölkopf Mark Ibrahim 34 10 0 15 Nov 2023
Causal Discovery under Latent Class Confounding Bijan Mazaheri Spencer Gordon Y. Rabani Leonard J. Schulman CML 18 2 0 13 Nov 2023
Multi-View Causal Representation Learning with Partial Observability Dingling Yao Danru Xu Sébastien Lachapelle Sara Magliacane Perouz Taslakian Georg Martius Julius von Kügelgen Francesco Locatello CML 37 30 0 07 Nov 2023
Complete collineations for maximum likelihood estimation Gergely Bérczi Eloise Hamilton Philipp Reichenbach A. Seigal 29 0 0 06 Nov 2023
Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions Simon Bing Urmi Ninad Jonas Wahl Jakob Runge CML 15 5 0 05 Nov 2023
Object-centric architectures enable efficient causal representation learning Amin Mansouri Jason S. Hartford Yan Zhang Yoshua Bengio CML OCL OOD 23 15 0 29 Oct 2023
Causal disentanglement of multimodal data Elise Walker Jonas A. Actor Carianne Martinez Nathaniel Trask CML 11 1 0 27 Oct 2023
Causal Representation Learning Made Identifiable by Grouping of Observational Variables H. Morioka Aapo Hyvarinen OOD CML BDL 27 9 0 24 Oct 2023
Identifiable Latent Polynomial Causal Models Through the Lens of Change Yuhang Liu Zhen Zhang Dong Gong Mingming Gong Biwei Huang A. Hengel Kun Zhang Javen Qinfeng Shi 22 13 0 24 Oct 2023
General Identifiability and Achievability for Causal Representation Learning Burak Varici Emre Acartürk Karthikeyan Shanmugam A. Tajer CML 35 16 0 24 Oct 2023
From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling Aneesh Komanduri Xintao Wu Yongkai Wu Feng Chen CML OOD 31 7 0 17 Oct 2023
Identifying Representations for Intervention Extrapolation Sorawit Saengkyongam Ezgi Ozyilkan Pradeep Ravikumar Niklas Pfister Jonas Peters CML OOD 16 14 0 06 Oct 2023
Multi-Domain Causal Representation Learning via Weak Distributional Invariances Kartik Ahuja Amin Mansouri Yixin Wang CML OOD 21 10 0 04 Oct 2023
Identifiability Guarantees for Causal Disentanglement from Soft Interventions Jiaqi Zhang C. Squires Kristjan Greenewald Akash Srivastava Karthikeyan Shanmugam Caroline Uhler CML 51 53 0 12 Jul 2023
Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation Sébastien Lachapelle Divyat Mahajan Ioannis Mitliagkas Simon Lacoste-Julien 34 25 0 05 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
Learning nonparametric latent causal graphs with unknown interventions Yibo Jiang Bryon Aragam CML 32 24 0 05 Jun 2023
Learning Linear Causal Representations from Interventions under General Nonlinear Mixing Simon Buchholz Goutham Rajendran Elan Rosenfeld Bryon Aragam Bernhard Schölkopf Pradeep Ravikumar CML 34 57 0 04 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
Neuro-Causal Factor Analysis Alex Markham Ming-Yu Liu Bryon Aragam Liam Solus CML 20 3 0 31 May 2023
Causal Component Analysis Wendong Liang Armin Kekić Julius von Kügelgen Simon Buchholz M. Besserve Luigi Gresele Bernhard Schölkopf CML 29 36 0 26 May 2023
Learning Causal Graphs via Monotone Triangular Transport Maps S. Akbari Luca Ganassali Negar Kiyavash OT CML 16 8 0 26 May 2023
Leveraging sparse and shared feature activations for disentangled representation learning Marco Fumero F. Wenzel L. Zancato Alessandro Achille Emanuele Rodolà Stefano Soatto Bernhard Schölkopf Francesco Locatello OOD DRL 34 22 0 17 Apr 2023
Unpaired Multi-Domain Causal Representation Learning Nils Sturma C. Squires Mathias Drton Caroline Uhler OOD CML 27 20 0 02 Feb 2023
Score-based Causal Representation Learning with Interventions Burak Varici Emre Acartürk Karthikeyan Shanmugam Abhishek Kumar A. Tajer CML 27 38 0 19 Jan 2023
Interventional Causal Representation Learning Kartik Ahuja Divyat Mahajan Yixin Wang Yoshua Bengio CML 39 83 0 24 Sep 2022
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