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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
Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Data
Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Data
Mouad El Bouchattaoui
Myriam Tami
Benoit Lepetit
P. Cournède
CMLOOD
483
2
0
16 Oct 2023
Machine Learning Who to Nudge: Causal vs Predictive Targeting in a Field
  Experiment on Student Financial Aid Renewal
Machine Learning Who to Nudge: Causal vs Predictive Targeting in a Field Experiment on Student Financial Aid RenewalJournal of Econometrics (JE), 2023
Susan Athey
Niall Keleher
Jann Spiess
159
21
0
12 Oct 2023
Statistical Performance Guarantee for Subgroup Identification with Generic Machine Learning
Statistical Performance Guarantee for Subgroup Identification with Generic Machine Learning
Michael Lingzhi Li
Kosuke Imai
CML
330
2
0
12 Oct 2023
Positivity-free Policy Learning with Observational Data
Positivity-free Policy Learning with Observational DataInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Pan Zhao
Antoine Chambaz
Julie Josse
Shu Yang
256
7
0
10 Oct 2023
Causal Inference with Conditional Front-Door Adjustment and Identifiable
  Variational Autoencoder
Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational AutoencoderInternational Conference on Learning Representations (ICLR), 2023
Ziqi Xu
Debo Cheng
Jiuyong Li
Jixue Liu
Lin Liu
Kui Yu
CML
201
20
0
03 Oct 2023
Towards Causal Foundation Model: on Duality between Causal Inference and
  Attention
Towards Causal Foundation Model: on Duality between Causal Inference and Attention
Jiaqi Zhang
Joel Jennings
Agrin Hilmkil
Nick Pawlowski
Cheng Zhang
Chao Ma
CML
358
17
0
01 Oct 2023
Targeting relative risk heterogeneity with causal forests
Targeting relative risk heterogeneity with causal forests
Vik Shirvaikar
Andrea Storås
Xi Lin
Chris Holmes
CML
208
1
0
26 Sep 2023
OpportunityFinder: A Framework for Automated Causal Inference
OpportunityFinder: A Framework for Automated Causal Inference
Huy Nguyen
Prince Grover
Devashish Khatwani
CML
136
1
0
22 Sep 2023
On the Actionability of Outcome Prediction
On the Actionability of Outcome PredictionAAAI Conference on Artificial Intelligence (AAAI), 2023
Lydia T. Liu
Solon Barocas
Jon Kleinberg
Karen Levy
OffRLCML
197
11
0
08 Sep 2023
Measuring, Interpreting, and Improving Fairness of Algorithms using
  Causal Inference and Randomized Experiments
Measuring, Interpreting, and Improving Fairness of Algorithms using Causal Inference and Randomized Experiments
James Enouen
Tianshu Sun
Yan Liu
FaML
257
0
0
04 Sep 2023
Consistency of Random Forest Type Algorithms under a Probabilistic
  Impurity Decrease Condition
Consistency of Random Forest Type Algorithms under a Probabilistic Impurity Decrease Condition
Ricardo Blum
M. Hiabu
E. Mammen
J. T. Meyer
199
3
0
04 Sep 2023
Fairness Implications of Heterogeneous Treatment Effect Estimation with
  Machine Learning Methods in Policy-making
Fairness Implications of Heterogeneous Treatment Effect Estimation with Machine Learning Methods in Policy-making
Patrick Rehill
Nicholas Biddle
SyDaCML
173
3
0
02 Sep 2023
Small Area Estimation with Random Forests and the LASSO
Small Area Estimation with Random Forests and the LASSO
Victoire Michal
J. Wakefield
A. M. Schmidt
Alicia C. Cavanaugh
Brian E. Robinson
J. Baumgartner
107
2
0
29 Aug 2023
Conformal Meta-learners for Predictive Inference of Individual Treatment
  Effects
Conformal Meta-learners for Predictive Inference of Individual Treatment EffectsNeural Information Processing Systems (NeurIPS), 2023
Ahmed Alaa
Zaid Ahmad
Mark van der Laan
CML
346
19
0
28 Aug 2023
Does Misclassifying Non-confounding Covariates as Confounders Affect the
  Causal Inference within the Potential Outcomes Framework?
Does Misclassifying Non-confounding Covariates as Confounders Affect the Causal Inference within the Potential Outcomes Framework?
Yonghe Zhao
Q. Huang
Shuai Fu
Huashan Sun
CML
107
1
0
22 Aug 2023
Data-Driven Allocation of Preventive Care With Application to Diabetes
  Mellitus Type II
Data-Driven Allocation of Preventive Care With Application to Diabetes Mellitus Type IIManufacturing & Service Operations Management (MSOM), 2023
Mathias Kraus
Stefan Feuerriegel
M. Saar-Tsechansky
121
18
0
14 Aug 2023
Optimally weighted average derivative effects
Optimally weighted average derivative effects
Oliver Hines
Karla Diaz-Ordaz
S. Vansteelandt
CML
315
4
0
10 Aug 2023
Pareto Invariant Representation Learning for Multimedia Recommendation
Pareto Invariant Representation Learning for Multimedia RecommendationACM Multimedia (ACM MM), 2023
Shanshan Huang
Haoxuan Li
Qingsong Li
Chunyuan Zheng
Li Liu
CML
335
18
0
09 Aug 2023
Variable importance for causal forests: breaking down the heterogeneity
  of treatment effects
Variable importance for causal forests: breaking down the heterogeneity of treatment effects
Clément Bénard
Julie Josse
CML
155
7
0
07 Aug 2023
VLUCI: Variational Learning of Unobserved Confounders for Counterfactual
  Inference
VLUCI: Variational Learning of Unobserved Confounders for Counterfactual Inference
Yonghe Zhao
Q. Huang
Siwei Wu
Yun Peng
Huashan Sun
BDLCML
146
0
0
02 Aug 2023
VISPUR: Visual Aids for Identifying and Interpreting Spurious
  Associations in Data-Driven Decisions
VISPUR: Visual Aids for Identifying and Interpreting Spurious Associations in Data-Driven DecisionsIEEE Transactions on Visualization and Computer Graphics (TVCG), 2023
Xian Teng
Yongsu Ahn
Y. Lin
CML
234
5
0
26 Jul 2023
A Look into Causal Effects under Entangled Treatment in Graphs:
  Investigating the Impact of Contact on MRSA Infection
A Look into Causal Effects under Entangled Treatment in Graphs: Investigating the Impact of Contact on MRSA InfectionKnowledge Discovery and Data Mining (KDD), 2023
Jing Ma
Chen Chen
A. Vullikanti
Ritwick Mishra
Gregory R. Madden
Daniel Borrajo
Jundong Li
CML
165
6
0
17 Jul 2023
Assisting Clinical Decisions for Scarcely Available Treatment via
  Disentangled Latent Representation
Assisting Clinical Decisions for Scarcely Available Treatment via Disentangled Latent RepresentationKnowledge Discovery and Data Mining (KDD), 2023
Bing Xue
A. Said
Ziqi Xu
Hanyang Liu
N. Shah
Hanqing Yang
Philip R. O. Payne
Chenyang Lu
229
7
0
06 Jul 2023
Identification of Causal Relationship between Amyloid-beta Accumulation
  and Alzheimer's Disease Progression via Counterfactual Inference
Identification of Causal Relationship between Amyloid-beta Accumulation and Alzheimer's Disease Progression via Counterfactual Inference
Haixing Dai
Mengxuan Hu
Qing Li
Lu Zhang
Lin Zhao
...
Manhua Liu
Shijie Zhao
Sheng Li
Tianming Liu
Xiang Li
CMLOOD
254
2
0
03 Jul 2023
Medoid splits for efficient random forests in metric spaces
Medoid splits for efficient random forests in metric spacesComputational Statistics & Data Analysis (CSDA), 2023
Matthieu Bulté
Helle Sorensen
156
8
0
29 Jun 2023
Incremental Profit per Conversion: a Response Transformation for Uplift
  Modeling in E-Commerce Promotions
Incremental Profit per Conversion: a Response Transformation for Uplift Modeling in E-Commerce Promotions
Hugo Manuel Proença
Felipe Moraes
194
5
0
23 Jun 2023
Should I Stop or Should I Go: Early Stopping with Heterogeneous
  Populations
Should I Stop or Should I Go: Early Stopping with Heterogeneous PopulationsNeural Information Processing Systems (NeurIPS), 2023
Hammaad Adam
Fan Yin
Huibin
Mary Hu
Neil A. Tenenholtz
Lorin Crawford
Lester W. Mackey
Allison Koenecke
251
5
0
20 Jun 2023
Treatment Effects in Extreme Regimes
Treatment Effects in Extreme Regimes
Ahmed Aloui
Ali Hasan
Yuting Ng
Miroslav Pajic
Vahid Tarokh
193
0
0
20 Jun 2023
Generalized Random Forests using Fixed-Point Trees
Generalized Random Forests using Fixed-Point Trees
David L. Fleischer
D. Stephens
Archer Y. Yang
157
0
0
20 Jun 2023
Can predictive models be used for causal inference?
Can predictive models be used for causal inference?
Maximilian Pichler
F. Hartig
OODCML
242
6
0
18 Jun 2023
A Survey of Contextual Optimization Methods for Decision Making under
  Uncertainty
A Survey of Contextual Optimization Methods for Decision Making under UncertaintyEuropean Journal of Operational Research (EJOR), 2023
Utsav Sadana
A. Chenreddy
Erick Delage
Alexandre Forel
Emma Frejinger
Thibaut Vidal
AI4CE
344
154
0
17 Jun 2023
Fair and Robust Estimation of Heterogeneous Treatment Effects for Policy
  Learning
Fair and Robust Estimation of Heterogeneous Treatment Effects for Policy LearningInternational Conference on Machine Learning (ICML), 2023
K. Kim
J. Zubizarreta
265
10
0
06 Jun 2023
Multi-Study R-Learner for Estimating Heterogeneous Treatment Effects
  Across Studies Using Statistical Machine Learning
Multi-Study R-Learner for Estimating Heterogeneous Treatment Effects Across Studies Using Statistical Machine Learning
Cathy Shyr
Boyu Ren
Prasad Patil
Giovanni Parmigiani
CML
340
2
0
01 Jun 2023
Learning Prescriptive ReLU Networks
Learning Prescriptive ReLU NetworksInternational Conference on Machine Learning (ICML), 2023
Wei-Ju Sun
Asterios Tsiourvas
297
3
0
01 Jun 2023
Sharp Bounds for Generalized Causal Sensitivity Analysis
Sharp Bounds for Generalized Causal Sensitivity AnalysisNeural Information Processing Systems (NeurIPS), 2023
Dennis Frauen
Valentyn Melnychuk
Stefan Feuerriegel
CML
375
25
0
26 May 2023
Dynamic Inter-treatment Information Sharing for Individualized Treatment
  Effects Estimation
Dynamic Inter-treatment Information Sharing for Individualized Treatment Effects EstimationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
V. Chauhan
Jiandong Zhou
Ghadeer O. Ghosheh
Soheila Molaei
David Clifton
355
13
0
25 May 2023
Meta-learning for heterogeneous treatment effect estimation with
  closed-form solvers
Meta-learning for heterogeneous treatment effect estimation with closed-form solversMachine-mediated learning (ML), 2023
Tomoharu Iwata
Yoichi Chikahara
CMLFedML
212
2
0
19 May 2023
Integrating Nearest Neighbors with Neural Network Models for Treatment
  Effect Estimation
Integrating Nearest Neighbors with Neural Network Models for Treatment Effect EstimationInternational Journal of Neural Systems (IJNS), 2023
Niki Kiriakidou
Christos Diou
CML
112
4
0
11 May 2023
An Efficient Doubly-Robust Test for the Kernel Treatment Effect
An Efficient Doubly-Robust Test for the Kernel Treatment EffectNeural Information Processing Systems (NeurIPS), 2023
Diego Martinez-Taboada
Aaditya Ramdas
Edward H. Kennedy
OOD
295
12
0
26 Apr 2023
Causal Effect Estimation with Variational AutoEncoder and the Front Door
  Criterion
Causal Effect Estimation with Variational AutoEncoder and the Front Door Criterion
Ziqi Xu
Debo Cheng
Jiuyong Li
Jixue Liu
Lin Liu
Kui Yu
CML
208
2
0
24 Apr 2023
Linking a predictive model to causal effect estimation
Linking a predictive model to causal effect estimation
Jiuyong Li
Lin Liu
Ziqi Xu
Ha Xuan Tran
T. Le
Jixue Liu
CML
189
0
0
10 Apr 2023
Combining experimental and observational data through a power likelihood
Combining experimental and observational data through a power likelihoodBiometrics (Biometrics), 2023
Xi Lin
J. Tarp
R. Evans
CML
187
7
0
05 Apr 2023
Matched Machine Learning: A Generalized Framework for Treatment Effect
  Inference With Learned Metrics
Matched Machine Learning: A Generalized Framework for Treatment Effect Inference With Learned Metrics
Marco Morucci
Cynthia Rudin
A. Volfovsky
CMLFedML
132
1
0
03 Apr 2023
Machine Learning for Economics Research: When What and How?
Machine Learning for Economics Research: When What and How?Social Science Research Network (SSRN), 2023
Ajit Desai
177
10
0
31 Mar 2023
A Novel Two-level Causal Inference Framework for On-road Vehicle Quality
  Issues Diagnosis
A Novel Two-level Causal Inference Framework for On-road Vehicle Quality Issues Diagnosis
Qian Wang
Huanyi Shui
Thi Tu Trinh Tran
Milad Zafar Nezhad
Devesh Upadhyay
K. Paynabar
An M. He
CML
112
0
0
31 Mar 2023
Practical Policy Optimization with Personalized Experimentation
Practical Policy Optimization with Personalized Experimentation
Mia Garrard
Hanson Wang
Benjamin Letham
Shaun Singh
Abbas Kazerouni
...
Yin Huang
Yichun Hu
Chad Zhou
Norm Zhou
E. Bakshy
134
0
0
30 Mar 2023
Comparison of Methods that Combine Multiple Randomized Trials to
  Estimate Heterogeneous Treatment Effects
Comparison of Methods that Combine Multiple Randomized Trials to Estimate Heterogeneous Treatment EffectsStatistics in Medicine (Stat Med), 2023
Carly L Brantner
Trang Quynh Nguyen
Tengjie Tang
Congwen Zhao
H. Hong
E. Stuart
179
10
0
28 Mar 2023
Adaptive Conformal Prediction by Reweighting Nonconformity Score
Adaptive Conformal Prediction by Reweighting Nonconformity Score
Salim I. Amoukou
Nicolas Brunel
365
17
0
22 Mar 2023
Learning When to Treat Business Processes: Prescriptive Process
  Monitoring with Causal Inference and Reinforcement Learning
Learning When to Treat Business Processes: Prescriptive Process Monitoring with Causal Inference and Reinforcement LearningInternational Conference on Advanced Information Systems Engineering (CAiSE), 2023
Z. Bozorgi
Marlon Dumas
M. Rosa
Artem Polyvyanyy
Mahmoud Shoush
Irene Teinemaa
CML
106
14
0
07 Mar 2023
DR-VIDAL -- Doubly Robust Variational Information-theoretic Deep Adversarial Learning for Counterfactual Prediction and Treatment Effect Estimation on Real World Data
DR-VIDAL -- Doubly Robust Variational Information-theoretic Deep Adversarial Learning for Counterfactual Prediction and Treatment Effect Estimation on Real World DataAmerican Medical Informatics Association Annual Symposium (AMIA), 2021
Shantanu Ghosh
Zheng Feng
Jiang Bian
Kevin R. B. Butler
M. Prosperi
CMLOODBDL
194
2
0
07 Mar 2023
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