v1v2v3 (latest)

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"

38 / 138 papers shown

Title
Learning causal representations for robust domain adaptation shuai Yang Kui Yu Fuyuan Cao Lin Liu Hongya Wang Jiuyong Li OOD CML TTA 71 44 0 12 Nov 2020
Causality-aware counterfactual confounding adjustment as an alternative to linear residualization in anticausal prediction tasks based on linear learners E. C. Neto OOD CML 61 6 0 09 Nov 2020
Stable predictions for health related anticausal prediction tasks affected by selection biases: the need to deconfound the test set features E. C. Neto Phil Snyder S. Sieberts L. Omberg CML OOD 16 1 0 09 Nov 2020
Underspecification Presents Challenges for Credibility in Modern Machine Learning Alexander DÁmour Katherine A. Heller D. Moldovan Ben Adlam B. Alipanahi ... Kellie Webster Steve Yadlowsky T. Yun Xiaohua Zhai D. Sculley OffRL 171 688 0 06 Nov 2020
Latent Causal Invariant Model Xinwei Sun Botong Wu Xiangyu Zheng Chang-Shu Liu Wei Chen Tao Qin Tie-Yan Liu OOD CML BDL 93 14 0 04 Nov 2020
Learning Causal Semantic Representation for Out-of-Distribution Prediction Chang-Shu Liu Xinwei Sun Jindong Wang Haoyue Tang Tao Li Tao Qin Wei Chen Tie-Yan Liu CML OODD OOD 153 106 0 03 Nov 2020
Domain adaptation under structural causal models Yuansi Chen Peter Buhlmann CML OOD AI4CE 132 40 0 29 Oct 2020
Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions Kartik Ahuja Karthikeyan Shanmugam Amit Dhurandhar 57 9 0 28 Oct 2020
Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction Shuxi Zeng Murat Ali Bayir Joel Pfeiffer Denis Xavier Charles Emre Kıcıman TTA 52 18 0 17 Oct 2020
Explaining The Efficacy of Counterfactually Augmented Data Divyansh Kaushik Amrith Rajagopal Setlur Eduard H. Hovy Zachary Chase Lipton CML 74 82 0 05 Oct 2020
Tackling unsupervised multi-source domain adaptation with optimism and consistency Diogo Pernes Jaime S. Cardoso 65 8 0 29 Sep 2020
CASTLE: Regularization via Auxiliary Causal Graph Discovery Trent Kyono Yao Zhang M. Schaar OOD CML 78 69 0 28 Sep 2020
Interventional Few-Shot Learning Zhongqi Yue Hanwang Zhang Qianru Sun Xiansheng Hua 113 234 0 28 Sep 2020
Multi-task Causal Learning with Gaussian Processes Virginia Aglietti Theodoros Damoulas Mauricio A. Alvarez Javier I. González CML 74 18 0 27 Sep 2020
Causal Bandits without prior knowledge using separating sets A. D. Kroon Danielle Belgrave Joris M. Mooij CML 42 23 0 16 Sep 2020
Accounting for Unobserved Confounding in Domain Generalization Alexis Bellot M. Schaar CML OOD 97 23 0 21 Jul 2020
Counterfactual Predictions under Runtime Confounding Amanda Coston Edward H. Kennedy Alexandra Chouldechova OOD OffRL 69 28 0 30 Jun 2020
Domain Generalization using Causal Matching Divyat Mahajan Shruti Tople Amit Sharma OOD 108 338 0 12 Jun 2020
An Analysis of the Adaptation Speed of Causal Models Rémi Le Priol Reza Babanezhad Harikandeh Yoshua Bengio Simon Lacoste-Julien CML 46 14 0 18 May 2020
Distributional robustness of K-class estimators and the PULSE M. E. Jakobsen J. Peters OOD 58 29 0 07 May 2020
Selecting Data Augmentation for Simulating Interventions Maximilian Ilse Jakub M. Tomczak Patrick Forré OOD CML 76 18 0 04 May 2020
Causal Transfer for Imitation Learning and Decision Making under Sensor-shift Jalal Etesami Philipp Geiger OffRL 54 15 0 02 Mar 2020
I-SPEC: An End-to-End Framework for Learning Transportable, Shift-Stable Models Adarsh Subbaswamy Suchi Saria OOD 71 14 0 20 Feb 2020
Invariant Risk Minimization Games Kartik Ahuja Karthikeyan Shanmugam Kush R. Varshney Amit Dhurandhar OOD 111 252 0 11 Feb 2020
Few-shot Domain Adaptation by Causal Mechanism Transfer Takeshi Teshima Issei Sato Masashi Sugiyama OOD CML TTA 101 86 0 10 Feb 2020
Domain Adaptation as a Problem of Inference on Graphical Models Kun Zhang Biwei Huang P. Stojanov Erdun Gao Qingsong Liu Clark Glymour OOD 104 66 0 09 Feb 2020
Improving Model Robustness Using Causal Knowledge T. Kyono M. Schaar OOD 65 12 0 27 Nov 2019
Causality for Machine Learning Bernhard Schölkopf CML AI4CE LRM 109 465 0 24 Nov 2019
Causality-based Feature Selection: Methods and Evaluations Kui Yu Xianjie Guo Lin Liu Jiuyong Li Hao Wang Zhaolong Ling Xindong Wu CML 90 97 0 17 Nov 2019
Fairness Violations and Mitigation under Covariate Shift Harvineet Singh Rina Singh Vishwali Mhasawade R. Chunara OOD 79 15 0 02 Nov 2019
Population-aware Hierarchical Bayesian Domain Adaptation via Multiple-component Invariant Learning Vishwali Mhasawade N. Rehman R. Chunara OOD 70 9 0 24 Aug 2019
Invariant Risk Minimization Martín Arjovsky Léon Bottou Ishaan Gulrajani David Lopez-Paz OOD 260 2,249 0 05 Jul 2019
Gradient-Based Neural DAG Learning Sébastien Lachapelle P. Brouillard T. Deleu Simon Lacoste-Julien BDL CML 124 276 0 05 Jun 2019
Semi-Supervised Learning, Causality and the Conditional Cluster Assumption Julius von Kügelgen A. Mey Marco Loog Bernhard Schölkopf CML 69 26 0 28 May 2019
A Unifying Causal Framework for Analyzing Dataset Shift-stable Learning Algorithms Adarsh Subbaswamy Bryant Chen Suchi Saria OOD 57 18 0 27 May 2019
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms Yoshua Bengio T. Deleu Nasim Rahaman Nan Rosemary Ke Sébastien Lachapelle O. Bilaniuk Anirudh Goyal C. Pal CML OOD 137 335 0 30 Jan 2019
A review of domain adaptation without target labels Wouter M. Kouw Marco Loog OOD VLM 56 491 0 16 Jan 2019
Preventing Failures Due to Dataset Shift: Learning Predictive Models That Transport Adarsh Subbaswamy Peter F. Schulam Suchi Saria OOD 86 20 0 11 Dec 2018