Identifying Representations for Intervention Extrapolation

6 October 2023

Niklas Pfister

Papers citing "Identifying Representations for Intervention Extrapolation"

38 / 38 papers shown

Title
Sanity Checking Causal Representation Learning on a Simple Real-World System Juan L. Gamella Simon Bing Jakob Runge CML 151 1 0 27 Feb 2025
Boosted Control Functions Nicola Gnecco Jonas Peters Sebastian Engelke Niklas Pfister 48 2 0 09 Oct 2023
Identifiability Guarantees for Causal Disentanglement from Soft Interventions Jiaqi Zhang C. Squires Kristjan Greenewald Akash Srivastava Karthikeyan Shanmugam Caroline Uhler CML 84 62 0 12 Jul 2023
Identification of Nonlinear Latent Hierarchical Models Lingjing Kong Erdun Gao Feng Xie Eric Xing Yuejie Chi Kun Zhang CML 47 20 0 13 Jun 2023
Intervention Generalization: A View from Factor Graph Models Gecia Bravo Hermsdorff David S. Watson Jialin Yu Jakob Zeitler Ricardo M. A. Silva CML 50 5 0 06 Jun 2023
Learning nonparametric latent causal graphs with unknown interventions Yibo Jiang Bryon Aragam CML 65 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 82 65 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 108 64 0 01 Jun 2023
Score-based Causal Representation Learning with Interventions Burak Varici Emre Acartürk Karthikeyan Shanmugam Abhishek Kumar A. Tajer CML 68 39 0 19 Jan 2023
Linear Causal Disentanglement via Interventions C. Squires A. Seigal Salil Bhate Caroline Uhler CML 70 68 0 29 Nov 2022
Interventional Causal Representation Learning Kartik Ahuja Divyat Mahajan Yixin Wang Yoshua Bengio CML 72 94 0 24 Sep 2022
Identifiability of deep generative models without auxiliary information Bohdan Kivva Goutham Rajendran Pradeep Ravikumar Bryon Aragam DRL 88 52 0 20 Jun 2022
Weakly Supervised Representation Learning with Sparse Perturbations Kartik Ahuja Jason S. Hartford Yoshua Bengio SSL 79 60 0 02 Jun 2022
Towards efficient representation identification in supervised learning Kartik Ahuja Divyat Mahajan Vasilis Syrgkanis Ioannis Mitliagkas CoGe OOD DRL 50 19 0 10 Apr 2022
Weakly supervised causal representation learning Johann Brehmer P. D. Haan Phillip Lippe Taco S. Cohen OOD CML 69 130 0 30 Mar 2022
Domain-Adjusted Regression or: ERM May Already Learn Features Sufficient for Out-of-Distribution Generalization Elan Rosenfeld Pradeep Ravikumar Andrej Risteski OOD 68 81 0 14 Feb 2022
Exploiting Independent Instruments: Identification and Distribution Generalization Sorawit Saengkyongam Leonard Henckel Niklas Pfister J. Peters 39 18 0 03 Feb 2022
Diffusion Autoencoders: Toward a Meaningful and Decodable Representation Konpat Preechakul Nattanat Chatthee Suttisak Wizadwongsa Supasorn Suwajanakorn SyDa DiffM 114 431 0 30 Nov 2021
Identifiable Deep Generative Models via Sparse Decoding Gemma E. Moran Dhanya Sridhar Yixin Wang David M. Blei BDL 52 48 0 20 Oct 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 85 139 0 21 Jul 2021
Learning latent causal graphs via mixture oracles Bohdan Kivva Goutham Rajendran Pradeep Ravikumar Bryon Aragam CML 76 48 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 60 65 0 17 Jun 2021
Operationalizing Complex Causes: A Pragmatic View of Mediation Limor Gultchin David S. Watson Matt J. Kusner Ricardo M. A. Silva CML 32 5 0 09 Jun 2021
The Risks of Invariant Risk Minimization Elan Rosenfeld Pradeep Ravikumar Andrej Risteski OOD 74 311 0 12 Oct 2020
On Linear Identifiability of Learned Representations Geoffrey Roeder Luke Metz Diederik P. Kingma CML 58 81 0 01 Jul 2020
Learning Joint Nonlinear Effects from Single-variable Interventions in the Presence of Hidden Confounders Sorawit Saengkyongam Ricardo M. A. Silva CML 20 10 0 23 May 2020
Distributional robustness of K-class estimators and the PULSE M. E. Jakobsen J. Peters OOD 34 29 0 07 May 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 298 934 0 02 Mar 2020
Kernel Conditional Moment Test via Maximum Moment Restriction Krikamol Muandet Wittawat Jitkrittum Jonas M. Kubler 44 25 0 21 Feb 2020
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 390 10,591 0 17 Feb 2020
Variational Autoencoders and Nonlinear ICA: A Unifying Framework Ilyes Khemakhem Diederik P. Kingma Ricardo Pio Monti Aapo Hyvarinen OOD 71 595 0 10 Jul 2019
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 179 2,223 0 05 Jul 2019
Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning Aapo Hyvarinen Hiroaki Sasaki Richard Turner OOD CML 92 330 0 22 May 2018
Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA Aapo Hyvarinen H. Morioka CML OOD AI4TS 61 409 0 20 May 2016
Extended Conditional Independence and Applications in Causal Inference Panayiota Constantinou A. Dawid CML 47 44 0 01 Dec 2015
Adversarial Autoencoders Alireza Makhzani Jonathon Shlens Navdeep Jaitly Ian Goodfellow Brendan J. Frey GAN 86 2,224 0 18 Nov 2015
Representation Learning: A Review and New Perspectives Yoshua Bengio Aaron Courville Pascal Vincent OOD SSL 256 12,435 0 24 Jun 2012
Kernels for Vector-Valued Functions: a Review Mauricio A. Alvarez Lorenzo Rosasco Neil D. Lawrence GP 207 925 0 30 Jun 2011