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Estimation and Inference of Heterogeneous Treatment Effects using Random
  Forests
v1v2v3v4 (latest)

Estimation and Inference of Heterogeneous Treatment Effects using Random Forests

14 October 2015
Stefan Wager
Susan Athey
    SyDaCML
ArXiv (abs)PDFHTML

Papers citing "Estimation and Inference of Heterogeneous Treatment Effects using Random Forests"

50 / 726 papers shown
Efficient Counterfactual Learning from Bandit Feedback
Efficient Counterfactual Learning from Bandit Feedback
Yusuke Narita
Shota Yasui
Kohei Yata
OffRL
295
49
0
10 Sep 2018
Optimal Nonparametric Inference with Two-Scale Distributional Nearest
  Neighbors
Optimal Nonparametric Inference with Two-Scale Distributional Nearest Neighbors
Emre Demirkaya
Yingying Fan
Lan Gao
Jinchi Lv
Patrick Vossler
Jingbo Wang
184
7
0
25 Aug 2018
Transfer Learning for Estimating Causal Effects using Neural Networks
Transfer Learning for Estimating Causal Effects using Neural Networks
Sören R. Künzel
Bradly C. Stadie
N. Vemuri
V. Ramakrishnan
Jasjeet Sekhon
Pieter Abbeel
CML
102
33
0
23 Aug 2018
Approximation Trees: Statistical Stability in Model Distillation
Approximation Trees: Statistical Stability in Model Distillation
Yichen Zhou
Zhengze Zhou
Giles Hooker
245
23
0
22 Aug 2018
Estimating Heterogeneous Causal Effects in the Presence of Irregular
  Assignment Mechanisms
Estimating Heterogeneous Causal Effects in the Presence of Irregular Assignment Mechanisms
Falco J. Bargagli-Stoffi
G. Gnecco
CML
127
10
0
13 Aug 2018
Semiparametric Bayesian causal inference
Semiparametric Bayesian causal inference
Kolyan Ray
A. van der Vaart
CML
176
9
0
13 Aug 2018
Linked Causal Variational Autoencoder for Inferring Paired Spillover
  Effects
Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects
Vineeth Rakesh
Ruocheng Guo
Raha Moraffah
Nitin Agarwal
Huan Liu
CMLBDL
208
44
0
09 Aug 2018
Local Linear Forests
Local Linear Forests
R. Friedberg
J. Tibshirani
Susan Athey
Stefan Wager
300
98
0
30 Jul 2018
Optimization over Continuous and Multi-dimensional Decisions with
  Observational Data
Optimization over Continuous and Multi-dimensional Decisions with Observational Data
Dimitris Bertsimas
Christopher McCord
218
27
0
11 Jul 2018
Cause-Effect Deep Information Bottleneck For Systematically Missing
  Covariates
Cause-Effect Deep Information Bottleneck For Systematically Missing Covariates
S. Parbhoo
Mario Wieser
Aleksander Wieczorek
Volker Roth
CML
284
5
0
06 Jul 2018
Boulevard: Regularized Stochastic Gradient Boosted Trees and Their
  Limiting Distribution
Boulevard: Regularized Stochastic Gradient Boosted Trees and Their Limiting Distribution
Yichen Zhou
Giles Hooker
UQCV
282
12
0
26 Jun 2018
Interpretable Almost Matching Exactly for Causal Inference
Interpretable Almost Matching Exactly for Causal Inference
Yameng Liu
Awa Dieng
Sudeepa Roy
Cynthia Rudin
A. Volfovsky
200
2
0
18 Jun 2018
Orthogonal Random Forest for Causal Inference
Orthogonal Random Forest for Causal Inference
Miruna Oprescu
Vasilis Syrgkanis
Zhiwei Steven Wu
CML
294
120
0
09 Jun 2018
Unbiased Estimation of the Value of an Optimized Policy
Unbiased Estimation of the Value of an Optimized Policy
Elon Portugaly
Joseph J. Pfeiffer
OffRL
40
0
0
07 Jun 2018
High-Dimensional Econometrics and Regularized GMM
High-Dimensional Econometrics and Regularized GMM
A. Belloni
Victor Chernozhukov
Denis Chetverikov
Christian B. Hansen
Kengo Kato
318
70
0
05 Jun 2018
Representation Balancing MDPs for Off-Policy Policy Evaluation
Representation Balancing MDPs for Off-Policy Policy Evaluation
Yao Liu
Omer Gottesman
Aniruddh Raghu
Matthieu Komorowski
A. Faisal
Finale Doshi-Velez
Emma Brunskill
OffRL
178
75
0
23 May 2018
Counterfactual Mean Embeddings
Counterfactual Mean Embeddings
Krikamol Muandet
Motonobu Kanagawa
Sorawit Saengkyongam
S. Marukatat
CMLOffRL
304
44
0
22 May 2018
Confounding-Robust Policy Improvement
Confounding-Robust Policy Improvement
Nathan Kallus
Angela Zhou
CMLOffRL
585
164
0
22 May 2018
Multiple Causal Inference with Latent Confounding
Multiple Causal Inference with Latent Confounding
Rajesh Ranganath
A. Perotte
CML
248
51
0
21 May 2018
The Blessings of Multiple Causes
The Blessings of Multiple Causes
Yixin Wang
David M. Blei
AI4CECML
263
307
0
17 May 2018
Sharp Analysis of a Simple Model for Random Forests
Sharp Analysis of a Simple Model for Random Forests
Jason M. Klusowski
FAtt
393
25
0
07 May 2018
Efficient Discovery of Heterogeneous Quantile Treatment Effects in
  Randomized Experiments via Anomalous Pattern Detection
Efficient Discovery of Heterogeneous Quantile Treatment Effects in Randomized Experiments via Anomalous Pattern Detection
E. McFowland
S. Somanchi
Daniel B. Neill
181
1
0
24 Mar 2018
Boosting Random Forests to Reduce Bias; One-Step Boosted Forest and its
  Variance Estimate
Boosting Random Forests to Reduce Bias; One-Step Boosted Forest and its Variance Estimate
Indrayudh Ghosal
Giles Hooker
381
51
0
21 Mar 2018
Minimax optimal rates for Mondrian trees and forests
Minimax optimal rates for Mondrian trees and forestsAnnals of Statistics (Ann. Stat.), 2018
Jaouad Mourtada
Stéphane Gaïffas
Erwan Scornet
333
50
0
15 Mar 2018
Uplift Modeling from Separate Labels
Uplift Modeling from Separate LabelsNeural Information Processing Systems (NeurIPS), 2018
Ikko Yamane
Florian Yger
Jamal Atif
Masashi Sugiyama
280
21
0
14 Mar 2018
A Minimax Surrogate Loss Approach to Conditional Difference Estimation
A Minimax Surrogate Loss Approach to Conditional Difference Estimation
Siong Thye Goh
Cynthia Rudin
83
6
0
10 Mar 2018
Learning Optimal Policies from Observational Data
Learning Optimal Policies from Observational Data
Onur Atan
W. Zame
M. Schaar
CMLOODOffRL
103
19
0
23 Feb 2018
Learning Weighted Representations for Generalization Across Designs
Learning Weighted Representations for Generalization Across Designs
Fredrik D. Johansson
Nathan Kallus
Uri Shalit
David Sontag
OOD
232
91
0
23 Feb 2018
DeepMatch: Balancing Deep Covariate Representations for Causal Inference
  Using Adversarial Training
DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Training
Nathan Kallus
CMLOOD
215
83
0
15 Feb 2018
Prophit: Causal inverse classification for multiple continuously valued
  treatment policies
Prophit: Causal inverse classification for multiple continuously valued treatment policies
Michael T. Lash
Qihang Lin
W. Street
CML
96
3
0
14 Feb 2018
How to Make Causal Inferences Using Texts
How to Make Causal Inferences Using Texts
Naoki Egami
Christian Fong
Justin Grimmer
Margaret E. Roberts
Brandon M Stewart
CML
248
167
0
06 Feb 2018
Estimation and Inference on Heterogeneous Treatment Effects in
  High-Dimensional Dynamic Panels under Weak Dependence
Estimation and Inference on Heterogeneous Treatment Effects in High-Dimensional Dynamic Panels under Weak DependenceQuantitative Economics (Quant. Econ.), 2017
Vira Semenova
Matt Goldman
Victor Chernozhukov
Matt Taddy
CML
500
16
0
28 Dec 2017
Bayesian Nonparametric Causal Inference: Information Rates and Learning
  Algorithms
Bayesian Nonparametric Causal Inference: Information Rates and Learning AlgorithmsIEEE Journal on Selected Topics in Signal Processing (JSTSP), 2017
Ahmed Alaa
Mihaela van der Schaar
CML
206
48
0
24 Dec 2017
Quasi-Oracle Estimation of Heterogeneous Treatment Effects
Quasi-Oracle Estimation of Heterogeneous Treatment Effects
Xinkun Nie
Stefan Wager
CML
581
763
0
13 Dec 2017
Fisher-Schultz Lecture: Generic Machine Learning Inference on
  Heterogenous Treatment Effects in Randomized Experiments, with an Application
  to Immunization in India
Fisher-Schultz Lecture: Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments, with an Application to Immunization in India
Victor Chernozhukov
Mert Demirer
E. Duflo
Iván Fernández-Val
CMLFedML
566
10
0
13 Dec 2017
Randomized incomplete $U$-statistics in high dimensions
Randomized incomplete UUU-statistics in high dimensions
Xiaohui Chen
Kengo Kato
252
46
0
03 Dec 2017
Causal nearest neighbor rules for optimal treatment regimes
Causal nearest neighbor rules for optimal treatment regimes
Xin Zhou
Michael R. Kosorok
CML
68
17
0
22 Nov 2017
Implicit Causal Models for Genome-wide Association Studies
Implicit Causal Models for Genome-wide Association StudiesInternational Conference on Learning Representations (ICLR), 2017
Dustin Tran
David M. Blei
CML
97
45
0
30 Oct 2017
Random Forests of Interaction Trees for Estimating Individualized
  Treatment Effects in Randomized Trials
Random Forests of Interaction Trees for Estimating Individualized Treatment Effects in Randomized Trials
X. Su
A. T. Peña
Lei Liu
R. Levine
CML
80
41
0
14 Sep 2017
A Practically Competitive and Provably Consistent Algorithm for Uplift
  Modeling
A Practically Competitive and Provably Consistent Algorithm for Uplift Modeling
Yan Zhao
X. Fang
D. Simchi-Levi
OffRL
106
21
0
12 Sep 2017
Consistency of survival tree and forest models: splitting bias and
  correction
Consistency of survival tree and forest models: splitting bias and correction
Yifan Cui
Ruoqing Zhu
Mai Zhou
Michael R. Kosorok
285
31
0
30 Jul 2017
FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal
  Inference
FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference
Tianyu Wang
Cynthia Rudin
M. Usaid Awan
Yameng Liu
Sudeepa Roy
Cynthia Rudin
A. Volfovsky
510
52
0
19 Jul 2017
Automated versus do-it-yourself methods for causal inference: Lessons
  learned from a data analysis competition
Automated versus do-it-yourself methods for causal inference: Lessons learned from a data analysis competition
Vincent Dorie
J. Hill
Uri Shalit
M. Scott
D. Cervone
CML
786
317
0
09 Jul 2017
Some methods for heterogeneous treatment effect estimation in
  high-dimensions
Some methods for heterogeneous treatment effect estimation in high-dimensions
Scott Powers
Junyang Qian
Kenneth Jung
Alejandro Schuler
N. Shah
Trevor Hastie
Robert Tibshirani
CML
181
236
0
01 Jul 2017
Targeted Undersmoothing
Targeted Undersmoothing
Christian B. Hansen
Damian Kozbur
S. Misra
214
14
0
22 Jun 2017
A Comparison of Resampling and Recursive Partitioning Methods in Random
  Forest for Estimating the Asymptotic Variance Using the Infinitesimal
  Jackknife
A Comparison of Resampling and Recursive Partitioning Methods in Random Forest for Estimating the Asymptotic Variance Using the Infinitesimal Jackknife
C. Brokamp
M. Rao
P. Ryan
R. Jandarov
83
5
0
19 Jun 2017
Deep Counterfactual Networks with Propensity-Dropout
Deep Counterfactual Networks with Propensity-Dropout
Ahmed Alaa
M. Weisz
M. Schaar
CMLOODBDL
116
90
0
19 Jun 2017
Gene Hunting with Knockoffs for Hidden Markov Models
Gene Hunting with Knockoffs for Hidden Markov Models
Matteo Sesia
C. Sabatti
Emmanuel J. Candès
192
146
0
14 Jun 2017
Meta-learners for Estimating Heterogeneous Treatment Effects using
  Machine Learning
Meta-learners for Estimating Heterogeneous Treatment Effects using Machine LearningProceedings of the National Academy of Sciences of the United States of America (PNAS), 2017
Sören R. Künzel
Jasjeet Sekhon
Peter J. Bickel
Bin Yu
CML
674
1,119
0
12 Jun 2017
A Deep Causal Inference Approach to Measuring the Effects of Forming
  Group Loans in Online Non-profit Microfinance Platform
A Deep Causal Inference Approach to Measuring the Effects of Forming Group Loans in Online Non-profit Microfinance Platform
T. T. Pham
Yuanyuan Shen
3DV
106
21
0
08 Jun 2017
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