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1605.03661
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Learning Representations for Counterfactual Inference
12 May 2016
Fredrik D. Johansson
Uri Shalit
David Sontag
CML
OOD
BDL
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Papers citing
"Learning Representations for Counterfactual Inference"
50 / 432 papers shown
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Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects
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395
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The Counterfactual
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Journal of Biomedical Informatics (JBI), 2020
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144
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Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data
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171
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Reducing Selection Bias in Counterfactual Reasoning for Individual Treatment Effects Estimation
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Qingfeng Lan
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181
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MetaCI: Meta-Learning for Causal Inference in a Heterogeneous Population
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Garima Gupta
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206
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Triply Robust Off-Policy Evaluation
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Anima Anandkumar
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172
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MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming
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L. Graham
Kostis Gourgoulias
Jonathan G. Richens
Ciarán M. Gilligan-Lee
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239
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Optimising Individual-Treatment-Effect Using Bandits
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72
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John Guttag
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139
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213
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163
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Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models
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Shota Yasui
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183
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Victoria Krakovna
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Andreas Maurer
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David Leslie
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Learning Individual Causal Effects from Networked Observational Data
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Wenlin Yao
Huan Liu
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282
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Reliable Estimation of Individual Treatment Effect with Causal Information Bottleneck
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Yong-Ho Baek
Sung Ju Hwang
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107
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Adapting Neural Networks for the Estimation of Treatment Effects
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David M. Blei
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495
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On the Fairness of Disentangled Representations
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Tom Rainforth
Stefan Bauer
Bernhard Schölkopf
Olivier Bachem
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178
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31 May 2019
Deep Generalized Method of Moments for Instrumental Variable Analysis
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Nathan Kallus
Tobias Schnabel
219
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28 May 2019
From What to How: An Initial Review of Publicly Available AI Ethics Tools, Methods and Research to Translate Principles into Practices
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Luciano Floridi
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Anat Elhalal
173
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Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models
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Michael Oberst
David Sontag
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340
184
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14 May 2019
Combining Parametric and Nonparametric Models for Off-Policy Evaluation
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Omer Gottesman
Yao Liu
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261
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Interpretable Subgroup Discovery in Treatment Effect Estimation with Application to Opioid Prescribing Guidelines
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Dennis L. Wei
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Monica Shekhar
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272
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Adversarial Balancing-based Representation Learning for Causal Effect Inference with Observational Data
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W. Duivesteijn
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178
49
0
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Active Learning for Decision-Making from Imbalanced Observational Data
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Peter F. Schulam
E. Siivola
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Suchi Saria
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182
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285
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274
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Cost-Effective Incentive Allocation via Structured Counterfactual Inference
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X. Yan
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234
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Learning Counterfactual Representations for Estimating Individual Dose-Response Curves
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Lorenz Linhardt
Stefan Bauer
J. M. Buhmann
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210
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A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms
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Yoshua Bengio
T. Deleu
Nasim Rahaman
Nan Rosemary Ke
Sébastien Lachapelle
O. Bilaniuk
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C. Pal
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472
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Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions
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Hao Wang
Berk Ustun
Flavio du Pin Calmon
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290
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0
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135
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Estimating Causal Effects With Partial Covariates For Clinical Interpretability
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Mario Wieser
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68
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Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search
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T. Weber
Yori Zwols
S. Racanière
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Jean-Baptiste Lespiau
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214
149
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Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction
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Daniel B. Neill
H. Nickisch
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172
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Adversarial Balancing for Causal Inference
Michal Ozery-Flato
Pierre Thodoroff
Matan Ninio
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T. El-Hay
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219
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Deep Reinforcement Learning
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356
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Perfect Match: A Simple Method for Learning Representations For Counterfactual Inference With Neural Networks
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A Survey of Learning Causality with Data: Problems and Methods
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54
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