Learning Linear Causal Representations from Interventions under General Nonlinear Mixing

4 June 2023

Papers citing "Learning Linear Causal Representations from Interventions under General Nonlinear Mixing"

48 / 48 papers shown

Title
Contextures: Representations from Contexts Runtian Zhai Kai Yang Che-Ping Tsai Burak Varici Zico Kolter Pradeep Ravikumar 74 0 0 02 May 2025
Robustness of Nonlinear Representation Learning Simon Buchholz Bernhard Schölkopf OOD 96 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 110 0 0 12 Mar 2025
Feature Matching Intervention: Leveraging Observational Data for Causal Representation Learning Haoze Li Jun Xie CML 56 0 0 05 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
Achievable distributional robustness when the robust risk is only partially identified Julia Kostin Nicola Gnecco Fanny Yang 64 3 0 04 Feb 2025
What is causal about causal models and representations? Frederik Hytting Jørgensen Luigi Gresele S. Weichwald CML 101 0 0 31 Jan 2025
Identification of Nonparametric Dynamic Causal Structure and Latent Process in Climate System Minghao Fu Biwei Huang Zijian Li Yujia Zheng Ignavier Ng Yingyao Hu Kun Zhang CML 40 0 0 21 Jan 2025
Identifiability Guarantees for Causal Disentanglement from Purely Observational Data Ryan Welch Jiaqi Zhang Caroline Uhler CML OOD 43 1 0 31 Oct 2024
Language Agents Meet Causality -- Bridging LLMs and Causal World Models John Gkountouras Matthias Lindemann Phillip Lippe E. Gavves Ivan Titov LRM 23 0 0 25 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 18 2 0 11 Sep 2024
Linear causal disentanglement via higher-order cumulants Paula Leyes Carreno Chiara Meroni A. Seigal CML 26 0 0 05 Jul 2024
ExDAG: Exact learning of DAGs Pavel Rytír Ales Wodecki Jakub Marecek CML 36 1 0 21 Jun 2024
Linear Causal Representation Learning from Unknown Multi-node Interventions Burak Varıcı Emre Acartürk Karthikeyan Shanmugam A. Tajer CML 22 1 0 09 Jun 2024
Smoke and Mirrors in Causal Downstream Tasks Riccardo Cadei Lukas Lindorfer Sylvia Cremer Cordelia Schmid Francesco Locatello CML 23 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 30 0 0 24 May 2024
Marrying Causal Representation Learning with Dynamical Systems for Science Dingling Yao Caroline Muller Francesco Locatello CML AI4CE 35 6 0 22 May 2024
Propensity Score Alignment of Unpaired Multimodal Data Johnny Xi Jason S. Hartford 19 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 27 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 27 13 0 13 Mar 2024
On the Origins of Linear Representations in Large Language Models Yibo Jiang Goutham Rajendran Pradeep Ravikumar Bryon Aragam Victor Veitch 59 24 0 06 Mar 2024
BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts Emanuele Marconato Samuele Bortolotti Emile van Krieken Antonio Vergari Andrea Passerini Stefano Teso 33 18 0 19 Feb 2024
Implicit Causal Representation Learning via Switchable Mechanisms Shayan Shirahmad Gale Bagi Zahra Gharaee Oliver Schulte Mark Crowley CML 42 0 0 16 Feb 2024
Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models Goutham Rajendran Simon Buchholz Bryon Aragam Bernhard Schölkopf Pradeep Ravikumar AI4CE 83 21 0 14 Feb 2024
Causal Representation Learning from Multiple Distributions: A General Setting Kun Zhang Shaoan Xie Ignavier Ng Yujia Zheng CML OOD 18 18 0 07 Feb 2024
Toward the Identifiability of Comparative Deep Generative Models Romain Lopez Jan-Christian Huetter Ehsan Hajiramezanali Jonathan Pritchard Aviv Regev 18 2 0 29 Jan 2024
Invariance & Causal Representation Learning: Prospects and Limitations Simon Bing Jonas Wahl Urmi Ninad Jakob Runge CML OOD 36 3 0 06 Dec 2023
An Interventional Perspective on Identifiability in Gaussian LTI Systems with Independent Component Analysis Goutham Rajendran Patrik Reizinger Wieland Brendel Pradeep Ravikumar CML 32 8 0 29 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 32 30 0 07 Nov 2023
Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions Simon Bing Urmi Ninad Jonas Wahl Jakob Runge CML 8 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 16 15 0 29 Oct 2023
Causal Representation Learning Made Identifiable by Grouping of Observational Variables H. Morioka Aapo Hyvarinen OOD CML BDL 15 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 15 13 0 24 Oct 2023
General Identifiability and Achievability for Causal Representation Learning Burak Varici Emre Acartürk Karthikeyan Shanmugam A. Tajer CML 24 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
Deep Backtracking Counterfactuals for Causally Compliant Explanations Klaus-Rudolf Kladny Julius von Kügelgen Bernhard Schölkopf Michael Muehlebach BDL 24 4 0 11 Oct 2023
Identifying Representations for Intervention Extrapolation Sorawit Saengkyongam Ezgi Ozyilkan Pradeep Ravikumar Niklas Pfister Jonas Peters CML OOD 11 14 0 06 Oct 2023
Multi-Domain Causal Representation Learning via Weak Distributional Invariances Kartik Ahuja Amin Mansouri Yixin Wang CML OOD 10 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 43 53 0 12 Jul 2023
Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation Sébastien Lachapelle Divyat Mahajan Ioannis Mitliagkas Simon Lacoste-Julien 29 25 0 05 Jul 2023
Identification of Nonlinear Latent Hierarchical Models Lingjing Kong Biwei Huang Feng Xie Eric P. Xing Yuejie Chi Kun Zhang CML 19 19 0 13 Jun 2023
Learning nonparametric latent causal graphs with unknown interventions Yibo Jiang Bryon Aragam CML 16 24 0 05 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 16 56 0 01 Jun 2023
Causal Component Analysis Wendong Liang Armin Kekić Julius von Kügelgen Simon Buchholz M. Besserve Luigi Gresele Bernhard Schölkopf CML 24 36 0 26 May 2023
Sparks of Artificial General Intelligence: Early experiments with GPT-4 Sébastien Bubeck Varun Chandrasekaran Ronen Eldan J. Gehrke Eric Horvitz ... Scott M. Lundberg Harsha Nori Hamid Palangi Marco Tulio Ribeiro Yi Zhang ELM AI4MH AI4CE ALM 239 2,232 0 22 Mar 2023
Posterior Collapse and Latent Variable Non-identifiability Yixin Wang David M. Blei John P. Cunningham CML DRL 75 70 0 02 Jan 2023
DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization Kevin Bello Bryon Aragam Pradeep Ravikumar 48 78 0 16 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