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Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions

20 July 2017

Joris M. Mooij

Papers citing "Domain Adaptation by Using Causal Inference to Predict Invariant Conditional Distributions"

50 / 138 papers shown

Title
Representation Learning Preserving Ignorability and Covariate Matching for Treatment Effects Praharsh Nanavati Ranjitha Prasad Karthikeyan Shanmugam OOD CML 125 0 0 29 Apr 2025
Causal DAG Summarization (Full Version) Anna Zeng Michael Cafarella Batya Kenig Markos Markakis Brit Youngmann Babak Salimi CML 57 2 0 21 Apr 2025
Partial Transportability for Domain Generalization Kasra Jalaldoust Alexis Bellot Elias Bareinboim OOD 130 6 0 30 Mar 2025
The Relativity of Causal Knowledge Gabriele DÁcunto Claudio Battiloro 53 0 0 13 Mar 2025
Achievable distributional robustness when the robust risk is only partially identified Julia Kostin Nicola Gnecco Fanny Yang 148 3 0 04 Feb 2025
Wasserstein-regularized Conformal Prediction under General Distribution Shift Rui Xu Chao Chen Yue Sun Parvathinathan Venkitasubramaniam Sihong Xie 120 1 0 23 Jan 2025
SSL Framework for Causal Inconsistency between Structures and Representations Hang Chen Xinyu Yang Keqing Du Wenya Wang 124 2 0 03 Jan 2025
Causal Invariance Learning via Efficient Optimization of a Nonconvex Objective Zhenyu Wang Yifan Hu Peter Buhlmann Zijian Guo 187 3 0 16 Dec 2024
Multi-environment Topic Models Dominic Sobhani Amir Feder David M. Blei 60 0 0 31 Oct 2024
Identifying General Mechanism Shifts in Linear Causal Representations Tianyu Chen Kevin Bello Francesco Locatello Bryon Aragam Pradeep Ravikumar OOD CML 89 3 0 31 Oct 2024
Considerations for Distribution Shift Robustness of Diagnostic Models in Healthcare Arno Blaas Adam Goliñski Andrew C. Miller Luca Zappella J. Jacobsen Christina Heinze-Deml OOD 74 0 0 25 Oct 2024
Efficient Identification of Direct Causal Parents via Invariance and Minimum Error Testing Minh Le Nguyen Mert R. Sabuncu 54 1 0 19 Sep 2024
Causal Discovery from Time-Series Data with Short-Term Invariance-Based Convolutional Neural Networks Rujia Shen Boran Wang Chao Zhao Yi Guan Jingchi Jiang CML BDL AI4TS 82 0 0 15 Aug 2024
Mind the Graph When Balancing Data for Fairness or Robustness Jessica Schrouff Alexis Bellot Amal Rannen-Triki Alan Malek Isabela Albuquerque Arthur Gretton Alexander DÁmour Silvia Chiappa OOD CML 112 3 0 25 Jun 2024
Learning When the Concept Shifts: Confounding, Invariance, and Dimension Reduction Kulunu Dharmakeerthi Y. Hur Tengyuan Liang 72 0 0 22 Jun 2024
Self-Distilled Disentangled Learning for Counterfactual Prediction Xinshu Li Mingming Gong Lina Yao CML 77 2 0 09 Jun 2024
Unbiased Faster R-CNN for Single-source Domain Generalized Object Detection Yajing Liu Shijun Zhou Xiyao Liu Chunhui Hao Baojie Fan Jiandong Tian ObjD 115 14 0 24 May 2024
Invariant Subspace Decomposition Margherita Lazzaretto Jonas Peters Niklas Pfister 93 0 0 15 Apr 2024
Proxy Methods for Domain Adaptation Katherine Tsai Stephen Pfohl Olawale Salaudeen Nicole Chiou Matt J. Kusner Alexander DÁmour Oluwasanmi Koyejo Arthur Gretton OOD 86 3 0 12 Mar 2024
OTClean: Data Cleaning for Conditional Independence Violations using Optimal Transport Alireza Pirhadi Mohammad Hossein Moslemi Alexander Cloninger Mostafa Milani Babak Salimi 75 5 0 04 Mar 2024
Evaluating and Correcting Performative Effects of Decision Support Systems via Causal Domain Shift Philip A. Boeken O. Zoeter Joris M. Mooij 123 1 0 01 Mar 2024
Towards Context-Aware Domain Generalization: Understanding the Benefits and Limits of Marginal Transfer Learning Jens Müller Lars Kühmichel Martin Rohbeck Stefan T. Radev Ullrich Kothe OOD 82 0 0 15 Dec 2023
Invariance & Causal Representation Learning: Prospects and Limitations Simon Bing Jonas Wahl Urmi Ninad Jakob Runge CML OOD 150 3 0 06 Dec 2023
Why Do Probabilistic Clinical Models Fail To Transport Between Sites? Thomas A. Lasko Eric V. Strobl William W Stead OOD 83 9 0 08 Nov 2023
Confounder Balancing in Adversarial Domain Adaptation for Pre-Trained Large Models Fine-Tuning Shuoran Jiang Qingcai Chen Yang Xiang Youcheng Pan Xiangping Wu AI4CE 126 1 0 24 Oct 2023
Specify Robust Causal Representation from Mixed Observations Mengyue Yang Xin-Qiang Cai Furui Liu Weinan Zhang Jun Wang CML OOD 111 7 0 21 Oct 2023
Data Augmentations for Improved (Large) Language Model Generalization Amir Feder Yoav Wald Claudia Shi Suchi Saria David M. Blei OOD CML 98 9 0 19 Oct 2023
Boosted Control Functions Nicola Gnecco Jonas Peters Sebastian Engelke Niklas Pfister 72 2 0 09 Oct 2023
Subspace Identification for Multi-Source Domain Adaptation Zijian Li Ruichu Cai Guan-Hong Chen Boyang Sun Zijian Li Kun Zhang 88 35 0 07 Oct 2023
Invariant Learning via Probability of Sufficient and Necessary Causes Mengyue Yang Zhen Fang Yonggang Zhang Yali Du Furui Liu Jean-François Ton Jianhong Wang Jun Wang OODD 132 14 0 22 Sep 2023
Prominent Roles of Conditionally Invariant Components in Domain Adaptation: Theory and Algorithms Keru Wu Yuansi Chen Wooseok Ha Ting Yu CML 80 2 0 19 Sep 2023
Loop Polarity Analysis to Avoid Underspecification in Deep Learning JR DONALD MARTIN St. Louis 41 0 0 18 Sep 2023
No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging Charles Jones Daniel Coelho De Castro Fabio De Sousa Ribeiro Ozan Oktay Melissa McCradden Ben Glocker FaML CML 108 9 0 31 Jul 2023
Causality-oriented robustness: exploiting general noise interventions Xinwei Shen Peter Buhlmann Armeen Taeb OOD 131 9 0 18 Jul 2023
Results on Counterfactual Invariance Jake Fawkes R. Evans 46 4 0 17 Jul 2023
Intervention Generalization: A View from Factor Graph Models Gecia Bravo Hermsdorff David S. Watson Jialin Yu Jakob Zeitler Ricardo M. A. Silva CML 77 6 0 06 Jun 2023
An Invariant Learning Characterization of Controlled Text Generation Carolina Zheng Claudia Shi Keyon Vafa Amir Feder David M. Blei OOD 98 8 0 31 May 2023
Shift-Robust Molecular Relational Learning with Causal Substructure Namkyeong Lee Kanghoon Yoon Gyoung S. Na Sein Kim Chanyoung Park 99 16 0 29 May 2023
Causal Information Splitting: Engineering Proxy Features for Robustness to Distribution Shifts Bijan Mazaheri Atalanti Mastakouri Dominik Janzing Mila Hardt OOD 87 4 0 10 May 2023
CMVAE: Causal Meta VAE for Unsupervised Meta-Learning Guodong Qi Huimin Yu CML SSL 79 5 0 20 Feb 2023
Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting Shayan Shirahmad Gale Bagi Zahra Gharaee Oliver Schulte Mark Crowley OODD OOD 78 13 0 17 Feb 2023
Discovering Optimal Scoring Mechanisms in Causal Strategic Prediction Tom Yan Shantanu Gupta Zachary Chase Lipton CML 61 1 0 14 Feb 2023
Generalized Invariant Matching Property via LASSO Kang Du Yu Xiang OOD 105 6 0 14 Jan 2023
Evaluation of Induced Expert Knowledge in Causal Structure Learning by NOTEARS Jawad Chowdhury Rezaur Rashid G. Terejanu CML 73 10 0 04 Jan 2023
Adapting to Latent Subgroup Shifts via Concepts and Proxies Ibrahim Alabdulmohsin Nicole Chiou Alexander DÁmour Arthur Gretton Sanmi Koyejo Matt J. Kusner Stephen Pfohl Olawale Salaudeen Jessica Schrouff Katherine Tsai 130 11 0 21 Dec 2022
$Interpretability and causal discovery of the machine learning models to predict the production of CBM wells after hydraulic fracturing$ Interpretability and causal discovery of the machine learning models to predict the production of CBM wells after hydraulic fracturing Chao Min Guo-quan Wen Liang Gou Xiaogang Li Zhaozhong Yang CML 34 12 0 21 Dec 2022
Causal Inference via Style Transfer for Out-of-distribution Generalisation Toan Nguyen Kien Do D. Nguyen Bao Duong T. Nguyen CML OODD OOD 72 10 0 06 Dec 2022
A Survey on Causal Representation Learning and Future Work for Medical Image Analysis Chang-Tien Lu OOD BDL CML MedIm 107 0 0 28 Oct 2022
Bridging Machine Learning and Sciences: Opportunities and Challenges Taoli Cheng UQCV OOD AI4CE 61 2 0 24 Oct 2022
Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment Chenxiao Yang Qitian Wu Qingsong Wen Zhiqiang Zhou Liang Sun Junchi Yan OODD OOD 83 22 0 24 Oct 2022