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Learning Representations for Counterfactual Inference

12 May 2016

Papers citing "Learning Representations for Counterfactual Inference"

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Title
Learning Fair and Transferable Representations L. Oneto Michele Donini Andreas Maurer Massimiliano Pontil FaML 165 19 0 25 Jun 2019
Understanding artificial intelligence ethics and safety David Leslie FaML AI4TS 94 380 0 11 Jun 2019
Learning Individual Causal Effects from Networked Observational Data Ruocheng Guo Wenlin Yao Huan Liu CML OOD 130 101 0 08 Jun 2019
Reliable Estimation of Individual Treatment Effect with Causal Information Bottleneck Sungyub Kim Yong-Ho Baek Sung Ju Hwang Eunho Yang CML 51 1 0 07 Jun 2019
Adapting Neural Networks for the Estimation of Treatment Effects Claudia Shi David M. Blei Victor Veitch CML 220 399 0 05 Jun 2019
On the Fairness of Disentangled Representations Francesco Locatello G. Abbati Tom Rainforth Stefan Bauer Bernhard Schölkopf Olivier Bachem FaML DRL 119 233 0 31 May 2019
Deep Generalized Method of Moments for Instrumental Variable Analysis Andrew Bennett Nathan Kallus Tobias Schnabel 135 131 0 29 May 2019
Matching on What Matters: A Pseudo-Metric Learning Approach to Matching Estimation in High Dimensions Gentry Johnson B. Quistorff Matt Goldman 25 0 0 28 May 2019
From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices Jessica Morley Luciano Floridi Libby Kinsey Anat Elhalal 98 58 0 15 May 2019
Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models Michael Oberst David Sontag CML OffRL 182 177 0 14 May 2019
Combining Parametric and Nonparametric Models for Off-Policy Evaluation Omer Gottesman Yao Liu Scott Sussex Emma Brunskill Finale Doshi-Velez OffRL 135 36 0 14 May 2019
Interpretable Subgroup Discovery in Treatment Effect Estimation with Application to Opioid Prescribing Guidelines Chirag Nagpal Dennis L. Wei B. Vinzamuri Monica Shekhar Sara E. Berger Subhro Das Kush R. Varshney CML 143 26 0 08 May 2019
Adversarial Balancing-based Representation Learning for Causal Effect Inference with Observational Data Xin Du Lei Sun W. Duivesteijn Alexander G. Nikolaev Mykola Pechenizkiy OOD CML 96 45 0 30 Apr 2019
Active Learning for Decision-Making from Imbalanced Observational Data Iiris Sundin Peter F. Schulam E. Siivola Aki Vehtari Suchi Saria Samuel Kaski OOD CML 118 29 0 10 Apr 2019
Multi-Differential Fairness Auditor for Black Box Classifiers Xavier Gitiaux Huzefa Rangwala FaML 76 7 0 18 Mar 2019
Classifying Treatment Responders Under Causal Effect Monotonicity Nathan Kallus CML 219 16 0 14 Feb 2019
Weighted Tensor Completion for Time-Series Causal Inference Debmalya Mandal David C. Parkes 118 2 0 12 Feb 2019
Cost-Effective Incentive Allocation via Structured Counterfactual Inference Romain Lopez Chenchen Li X. Yan Junwu Xiong Michael I. Jordan Yuan Qi Le Song OffRL 158 17 0 07 Feb 2019
Learning Counterfactual Representations for Estimating Individual Dose-Response Curves Patrick Schwab Lorenz Linhardt Stefan Bauer J. M. Buhmann W. Karlen CML OOD 129 140 0 03 Feb 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 248 343 0 30 Jan 2019
Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions Hao Wang Berk Ustun Flavio du Pin Calmon FaML 170 89 0 29 Jan 2019
Learning Interpretable Models with Causal Guarantees Carolyn Kim Osbert Bastani FaML OOD CML 88 17 0 24 Jan 2019
Estimating Causal Effects With Partial Covariates For Clinical Interpretability S. Parbhoo Mario Wieser Volker Roth CML 36 0 0 26 Nov 2018
Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search Lars Buesing T. Weber Yori Zwols S. Racanière A. Guez Jean-Baptiste Lespiau N. Heess CML 157 144 0 15 Nov 2018
Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction William Herlands Daniel B. Neill H. Nickisch A. Wilson OOD 84 2 0 28 Oct 2018
Adversarial Balancing for Causal Inference Michal Ozery-Flato Pierre Thodoroff Matan Ninio Michal Rosen-Zvi T. El-Hay CML GAN 152 27 0 17 Oct 2018
Deep Reinforcement Learning Yuxi Li VLM OffRL 239 144 0 15 Oct 2018
Perfect Match: A Simple Method for Learning Representations For Counterfactual Inference With Neural Networks Patrick Schwab Lorenz Linhardt W. Karlen CML BDL 130 113 0 01 Oct 2018
Deep Neural Networks for Estimation and Inference M. Farrell Tengyuan Liang S. Misra BDL 253 260 0 26 Sep 2018
A Survey of Learning Causality with Data: Problems and Methods Ruocheng Guo Lu Cheng Jundong Li P. R. Hahn Huan Liu CML 154 174 0 25 Sep 2018
Fairness Through Causal Awareness: Learning Latent-Variable Models for Biased Data David Madras Elliot Creager T. Pitassi R. Zemel FaML 111 135 0 07 Sep 2018
Robust Counterfactual Inferences using Feature Learning and their Applications A. Mitra Kannan Achan Sushant Kumar CML OffRL 38 0 0 22 Aug 2018
Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects Vineeth Rakesh Ruocheng Guo Raha Moraffah Nitin Agarwal Huan Liu CML BDL 111 44 0 09 Aug 2018
Improving pairwise comparison models using Empirical Bayes shrinkage Stephen Ragain A. Peysakhovich J. Ugander 72 6 0 24 Jul 2018
Cause-Effect Deep Information Bottleneck For Systematically Missing Covariates S. Parbhoo Mario Wieser Aleksander Wieczorek Volker Roth CML 103 5 0 06 Jul 2018
A Primer on Causal Analysis Finnian Lattimore Cheng Soon Ong CML 40 7 0 05 Jun 2018
Representation Balancing MDPs for Off-Policy Policy Evaluation Yao Liu Omer Gottesman Aniruddh Raghu Matthieu Komorowski A. Faisal Finale Doshi-Velez Emma Brunskill OffRL 110 75 0 23 May 2018
Counterfactual Mean Embeddings Krikamol Muandet Motonobu Kanagawa Sorawit Saengkyongam S. Marukatat CML OffRL 192 43 0 22 May 2018
Multiple Causal Inference with Latent Confounding Rajesh Ranganath A. Perotte CML 165 50 0 21 May 2018
Uplift Modeling from Separate Labels Ikko Yamane Florian Yger Jamal Atif Masashi Sugiyama 145 21 0 14 Mar 2018
A Minimax Surrogate Loss Approach to Conditional Difference Estimation Siong Thye Goh Cynthia Rudin 62 6 0 10 Mar 2018
Active Learning with Logged Data Songbai Yan Kamalika Chaudhuri T. Javidi 174 27 0 25 Feb 2018
Learning Optimal Policies from Observational Data Onur Atan W. Zame M. Schaar CML OOD OffRL 84 18 0 23 Feb 2018
Learning Weighted Representations for Generalization Across Designs Fredrik D. Johansson Nathan Kallus Uri Shalit David Sontag OOD 158 90 0 23 Feb 2018
DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Training Nathan Kallus CML OOD 138 79 0 15 Feb 2018
Prophit: Causal inverse classification for multiple continuously valued treatment policies Michael T. Lash Qihang Lin W. Street CML 70 3 0 14 Feb 2018
A Gaussian process framework for overlap and causal effect estimation with high-dimensional covariates D. Ghosh Efrén Cruz-Cortés 63 0 0 09 Jan 2018
Bayesian Nonparametric Causal Inference: Information Rates and Learning Algorithms Ahmed Alaa Mihaela van der Schaar CML 104 45 0 24 Dec 2017
Extreme Dimension Reduction for Handling Covariate Shift Fulton Wang Cynthia Rudin 61 1 0 29 Nov 2017
Implicit Causal Models for Genome-wide Association Studies Dustin Tran David M. Blei CML 77 43 0 30 Oct 2017