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Identifiability Guarantees for Causal Disentanglement from Soft Interventions

12 July 2023

Jiaqi Zhang

C. Squires

Kristjan Greenewald

Akash Srivastava

Karthikeyan Shanmugam

Caroline Uhler

CML

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Papers citing "Identifiability Guarantees for Causal Disentanglement from Soft Interventions"

24 / 24 papers shown

Title
Towards Identifiability of Interventional Stochastic Differential Equations Aaron Zweig Zaikang Lin Elham Azizi David A. Knowles 62 1 0 21 May 2025
Sanity Checking Causal Representation Learning on a Simple Real-World System Juan L. Gamella Simon Bing Jakob Runge CML 183 1 0 27 Feb 2025
All or None: Identifiable Linear Properties of Next-token Predictors in Language Modeling Emanuele Marconato Sébastien Lachapelle Sebastian Weichwald Luigi Gresele 122 4 0 30 Oct 2024
Amortized Inference of Causal Models via Conditional Fixed-Point Iterations Divyat Mahajan Jannes Gladrow Agrin Hilmkil Cheng Zhang M. Scetbon 113 2 0 08 Oct 2024
Smoke and Mirrors in Causal Downstream Tasks Riccardo Cadei Lukas Lindorfer Sylvia Cremer Cordelia Schmid Francesco Locatello CML 99 6 0 27 May 2024
Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms Aneesh Komanduri Yongkai Wu Feng Chen Xintao Wu CML OOD 66 10 0 02 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 125 64 0 01 Jun 2023
Neuro-Causal Factor Analysis Alex Markham Ming-Yuan Liu Bryon Aragam Liam Solus CML 59 3 0 31 May 2023
Causal Structure Learning: a Combinatorial Perspective C. Squires Caroline Uhler CML 87 47 0 02 Jun 2022
Weakly Supervised Representation Learning with Sparse Perturbations Kartik Ahuja Jason S. Hartford Yoshua Bengio SSL 90 61 0 02 Jun 2022
The interventional Bayesian Gaussian equivalent score for Bayesian causal inference with unknown soft interventions Jack Kuipers G. Moffa CML 39 6 0 05 May 2022
Weakly supervised causal representation learning Johann Brehmer P. D. Haan Phillip Lippe Taco S. Cohen OOD CML 88 131 0 30 Mar 2022
Learning latent causal graphs via mixture oracles Bohdan Kivva Goutham Rajendran Pradeep Ravikumar Bryon Aragam CML 78 48 0 29 Jun 2021
DiBS: Differentiable Bayesian Structure Learning Lars Lorch Jonas Rothfuss Bernhard Schölkopf Andreas Krause 52 88 0 25 May 2021
Unsuitability of NOTEARS for Causal Graph Discovery Marcus Kaiser Maksim Sipos CML 98 66 0 12 Apr 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 115 303 0 03 Mar 2021
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 195 2,242 0 05 Jul 2019
Gradient-Based Neural DAG Learning Sébastien Lachapelle P. Brouillard T. Deleu Simon Lacoste-Julien BDL CML 64 275 0 05 Jun 2019
Sliced Wasserstein Generative Models Jiqing Wu Zhiwu Huang Dinesh Acharya Wen Li Janine Thoma D. Paudel Luc Van Gool DiffM 120 126 0 10 Apr 2019
Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning Aapo Hyvarinen Hiroaki Sasaki Richard Turner OOD CML 97 331 0 22 May 2018
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction Leland McInnes John Healy James Melville 199 9,473 0 09 Feb 2018
Consistency Guarantees for Greedy Permutation-Based Causal Inference Algorithms Liam Solus Yuhao Wang Caroline Uhler CML 68 79 0 12 Feb 2017
Causal Discovery from Changes Jin Tian Judea Pearl CML 118 165 0 10 Jan 2013
Geometry of the faithfulness assumption in causal inference Caroline Uhler Garvesh Raskutti Peter Buhlmann B. Yu 117 222 0 02 Jul 2012