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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
Uplift Modeling Under Limited Supervision
Uplift Modeling Under Limited Supervision
G. Panagopoulos
Daniele Malitesta
Fragkiskos D. Malliaros
Jun Pang
CML
352
2
0
28 Mar 2024
Contrastive Balancing Representation Learning for Heterogeneous
  Dose-Response Curves Estimation
Contrastive Balancing Representation Learning for Heterogeneous Dose-Response Curves Estimation
Minqin Zhu
Anpeng Wu
Haoxuan Li
Ruoxuan Xiong
Bo Li
...
Xuan Qin
Peng Zhen
Jiecheng Guo
Leilei Gan
Kun Kuang
CML
194
12
0
21 Mar 2024
Using Causal Trees to Estimate Personalized Task Difficulty in
  Post-Stroke Individuals
Using Causal Trees to Estimate Personalized Task Difficulty in Post-Stroke Individuals
N. Dennler
Stefanos Nikolaidis
Maja J. Matarić
85
1
0
06 Mar 2024
Triple/Debiased Lasso for Statistical Inference of Conditional Average
  Treatment Effects
Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects
Masahiro Kato
CML
293
1
0
05 Mar 2024
Applied Causal Inference Powered by ML and AI
Applied Causal Inference Powered by ML and AI
Victor Chernozhukov
Christian Hansen
Nathan Kallus
Martin Spindler
Vasilis Syrgkanis
CML
336
48
0
04 Mar 2024
Defining Expertise: Applications to Treatment Effect Estimation
Defining Expertise: Applications to Treatment Effect Estimation
Alihan Huyuk
Qiyao Wei
Alicia Curth
M. Schaar
CML
231
3
0
01 Mar 2024
Unveiling the Potential of Robustness in Evaluating Causal Inference
  Models
Unveiling the Potential of Robustness in Evaluating Causal Inference Models
Yiyan Huang
Cheuk Hang Leung
Siyi Wang
Yijun Li
Qi Wu
OODCML
201
1
0
28 Feb 2024
Federated Learning for Estimating Heterogeneous Treatment Effects
Federated Learning for Estimating Heterogeneous Treatment Effects
Disha Makhija
Joydeep Ghosh
Yejin Kim
CMLFedML
376
3
0
27 Feb 2024
Benchmarking Observational Studies with Experimental Data under
  Right-Censoring
Benchmarking Observational Studies with Experimental Data under Right-Censoring
Ilker Demirel
E. Brouwer
Zeshan Hussain
Michael Oberst
Anthony Philippakis
David Sontag
161
5
0
23 Feb 2024
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation
Jikai Jin
Vasilis Syrgkanis
CML
567
6
0
22 Feb 2024
Towards AI-Based Precision Oncology: A Machine Learning Framework for Personalized Counterfactual Treatment Suggestions based on Multi-Omics Data
Manuel Schürch
Laura Boos
V. Heinzelmann-Schwarz
Gabriele Gut
Michael Krauthammer
Andreas Wicki
Tumor Profiler Consortium
213
6
0
19 Feb 2024
Evaluating the Effectiveness of Index-Based Treatment Allocation
Evaluating the Effectiveness of Index-Based Treatment Allocation
Niclas Boehmer
Yash Nair
Sanket Shah
Lucas Janson
Aparna Taneja
Milind Tambe
198
5
0
19 Feb 2024
Conformal Convolution and Monte Carlo Meta-learners for Predictive Inference of Individual Treatment Effects
Conformal Convolution and Monte Carlo Meta-learners for Predictive Inference of Individual Treatment Effects
Jef Jonkers
Jarne Verhaeghe
Glenn Van Wallendael
Luc Duchateau
Sofie Van Hoecke
744
5
0
07 Feb 2024
The Essential Role of Causality in Foundation World Models for Embodied
  AI
The Essential Role of Causality in Foundation World Models for Embodied AI
Tarun Gupta
Wenbo Gong
Chao Ma
Nick Pawlowski
Agrin Hilmkil
...
Jianfeng Gao
Stefan Bauer
Danica Kragic
Bernhard Schölkopf
Cheng Zhang
289
28
0
06 Feb 2024
Entire Chain Uplift Modeling with Context-Enhanced Learning for Intelligent Marketing
Entire Chain Uplift Modeling with Context-Enhanced Learning for Intelligent Marketing
Yinqiu Huang
Shuli Wang
Min Gao
Xue Wei
Changhao Li
Chuan Luo
Yinhua Zhu
Xiong Xiao
Yi Luo
175
7
0
04 Feb 2024
Why do Random Forests Work? Understanding Tree Ensembles as
  Self-Regularizing Adaptive Smoothers
Why do Random Forests Work? Understanding Tree Ensembles as Self-Regularizing Adaptive Smoothers
Alicia Curth
Alan Jeffares
M. Schaar
UQCV
220
17
0
02 Feb 2024
Hierarchical Bias-Driven Stratification for Interpretable Causal Effect
  Estimation
Hierarchical Bias-Driven Stratification for Interpretable Causal Effect Estimation
Lucile Ter-Minassian
Liran Szlak
Ehud Karavani
Chris Holmes
Y. Shimoni
165
2
0
31 Jan 2024
Individualized Multi-Treatment Response Curves Estimation using RBF-net
  with Shared Neurons
Individualized Multi-Treatment Response Curves Estimation using RBF-net with Shared Neurons
Peter Chang
Arkaprava Roy
CML
305
1
0
29 Jan 2024
M$^3$TN: Multi-gate Mixture-of-Experts based Multi-valued Treatment
  Network for Uplift Modeling
M3^33TN: Multi-gate Mixture-of-Experts based Multi-valued Treatment Network for Uplift ModelingIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024
Zexu Sun
Xu Chen
164
9
0
24 Jan 2024
Subgroup analysis methods for time-to-event outcomes in heterogeneous
  randomized controlled trials
Subgroup analysis methods for time-to-event outcomes in heterogeneous randomized controlled trials
Valentine Perrin
Nathan Noiry
Nicolas Loiseau
Alex Nowak
CML
199
1
0
22 Jan 2024
Privacy Preserving Adaptive Experiment Design
Privacy Preserving Adaptive Experiment DesignInternational Conference on Machine Learning (ICML), 2024
Jiachun Li
Kaining Shi
David Simchi-Levi
473
1
0
16 Jan 2024
Treatment-Aware Hyperbolic Representation Learning for Causal Effect
  Estimation with Social Networks
Treatment-Aware Hyperbolic Representation Learning for Causal Effect Estimation with Social NetworksSDM (SDM), 2024
Ziqiang Cui
Xing Tang
Yang Qiao
Bowei He
Liang Chen
Xiuqiang He
Chen Ma
CML
237
0
0
12 Jan 2024
Disentangle Estimation of Causal Effects from Cross-Silo Data
Disentangle Estimation of Causal Effects from Cross-Silo DataIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2024
Yuxuan Liu
Yining Qi
Shuang Wang
Zhiming He
Wenchao Xu
Jialiang Zhu
Fan Yang
CML
168
4
0
04 Jan 2024
Is Knowledge All Large Language Models Needed for Causal Reasoning?
Is Knowledge All Large Language Models Needed for Causal Reasoning?
Hengrui Cai
Shengjie Liu
Rui Song
LRMELM
473
20
0
30 Dec 2023
Maximizing the Success Probability of Policy Allocations in Online
  Systems
Maximizing the Success Probability of Policy Allocations in Online Systems
Artem Betlei
Mariia Vladimirova
Mehdi Sebbar
Nicolas Urien
Thibaud Rahier
Benjamin Heymann
OffRL
149
5
0
26 Dec 2023
Estimation of individual causal effects in network setup for multiple
  treatments
Estimation of individual causal effects in network setup for multiple treatments
Abhinav Thorat
Ravi Kolla
N. Pedanekar
N. Onoe
CML
98
3
0
18 Dec 2023
Uncertainty Quantification in Heterogeneous Treatment Effect Estimation
  with Gaussian-Process-Based Partially Linear Model
Uncertainty Quantification in Heterogeneous Treatment Effect Estimation with Gaussian-Process-Based Partially Linear ModelAAAI Conference on Artificial Intelligence (AAAI), 2023
Shunsuke Horii
Yoichi Chikahara
187
6
0
16 Dec 2023
Disentangled Latent Representation Learning for Tackling the Confounding
  M-Bias Problem in Causal Inference
Disentangled Latent Representation Learning for Tackling the Confounding M-Bias Problem in Causal InferenceIndustrial Conference on Data Mining (IDM), 2023
Debo Cheng
Yang Xie
Ziqi Xu
Jiuyong Li
Lin Liu
Jixue Liu
Yinghao Zhang
Zaiwen Feng
CMLBDL
217
4
0
08 Dec 2023
The impact of heteroskedasticity on uplift modeling
The impact of heteroskedasticity on uplift modeling
B. Bokelmann
Stefan Lessmann
111
0
0
08 Dec 2023
Assessing the Usability of GutGPT: A Simulation Study of an AI Clinical
  Decision Support System for Gastrointestinal Bleeding Risk
Assessing the Usability of GutGPT: A Simulation Study of an AI Clinical Decision Support System for Gastrointestinal Bleeding Risk
Colleen E Chan
Kisung You
Sunny Chung
Mauro Giuffré
Theo Saarinen
...
Loren Laine
Ambrose H. Wong
Rene F. Kizilcec
Jasjeet Sekhon
Dennis L. Shung
LM&MAAI4MH
108
6
0
06 Dec 2023
Domain constraints improve risk prediction when outcome data is missing
Domain constraints improve risk prediction when outcome data is missing
S. Balachandar
Nikhil Garg
Emma Pierson
CMLOOD
347
10
0
06 Dec 2023
Adaptive Instrument Design for Indirect Experiments
Adaptive Instrument Design for Indirect ExperimentsInternational Conference on Learning Representations (ICLR), 2023
Yash Chandak
Shiv Shankar
Vasilis Syrgkanis
Emma Brunskill
224
5
0
05 Dec 2023
When accurate prediction models yield harmful self-fulfilling prophecies
When accurate prediction models yield harmful self-fulfilling prophecies
Wouter A. C. van Amsterdam
N. Geloven
Jesse H. Krijthe
Rajesh Ranganath
Giovanni Cina
467
17
0
02 Dec 2023
Adversarial Distribution Balancing for Counterfactual Reasoning
Adversarial Distribution Balancing for Counterfactual Reasoning
Stefan Schrod
Fabian H. Sinz
Michael Altenbuchinger
OODCML
240
1
0
28 Nov 2023
A Neural Framework for Generalized Causal Sensitivity Analysis
A Neural Framework for Generalized Causal Sensitivity AnalysisInternational Conference on Learning Representations (ICLR), 2023
Dennis Frauen
F. Imrie
Alicia Curth
Valentyn Melnychuk
Stefan Feuerriegel
M. Schaar
CML
307
11
0
27 Nov 2023
Bounds on Representation-Induced Confounding Bias for Treatment Effect
  Estimation
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation
Valentyn Melnychuk
Dennis Frauen
Stefan Feuerriegel
CML
327
19
0
19 Nov 2023
Business Policy Experiments using Fractional Factorial Designs: Consumer
  Retention on DoorDash
Business Policy Experiments using Fractional Factorial Designs: Consumer Retention on DoorDashKnowledge Discovery and Data Mining (KDD), 2023
Yixin Tang
Yicong Lin
Navdeep S. Sahni
160
0
0
10 Nov 2023
Distribution-uniform anytime-valid sequential inference
Distribution-uniform anytime-valid sequential inference
Ian Waudby-Smith
Edward H. Kennedy
Aaditya Ramdas
285
1
0
06 Nov 2023
Estimating treatment effects from single-arm trials via latent-variable
  modeling
Estimating treatment effects from single-arm trials via latent-variable modelingInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Manuel Haussmann
Tran Minh Son Le
Viivi Halla-aho
Samu Kurki
Jussi Leinonen
Miika Koskinen
Samuel Kaski
Harri Lähdesmäki
CML
366
0
0
06 Nov 2023
An Interdisciplinary Outlook on Large Language Models for Scientific
  Research
An Interdisciplinary Outlook on Large Language Models for Scientific Research
James Boyko
Joseph Cohen
Nathan Fox
Maria Han Veiga
Jennifer I-Hsiu Li
...
Andreas H. Rauch
Kenneth N. Reid
Soumi Tribedi
Anastasia Visheratina
Xin Xie
245
24
0
03 Nov 2023
High Precision Causal Model Evaluation with Conditional Randomization
High Precision Causal Model Evaluation with Conditional RandomizationNeural Information Processing Systems (NeurIPS), 2023
Chao Ma
Cheng Zhang
CML
141
1
0
03 Nov 2023
Causal inference with Machine Learning-Based Covariate Representation
Causal inference with Machine Learning-Based Covariate Representation
Yuhang Wu
Jinghai He
Zeyu Zheng
CML
164
0
0
03 Nov 2023
A Review and Roadmap of Deep Causal Model from Different Causal
  Structures and Representations
A Review and Roadmap of Deep Causal Model from Different Causal Structures and Representations
Hang Chen
Keqing Du
Chenguang Li
Xinyu Yang
338
3
0
02 Nov 2023
Personalized Assignment to One of Many Treatment Arms via Regularized
  and Clustered Joint Assignment Forests
Personalized Assignment to One of Many Treatment Arms via Regularized and Clustered Joint Assignment Forests
Rahul Ladhania
Jann Spiess
Lyle Ungar
Wenbo Wu
CML
138
1
0
01 Nov 2023
Optimal Transport for Treatment Effect Estimation
Optimal Transport for Treatment Effect EstimationNeural Information Processing Systems (NeurIPS), 2023
Hao Wang
Zhichao Chen
Jiajun Fan
Haoxuan Li
Tianqiao Liu
Weiming Liu
Quanyu Dai
Yichao Wang
Zhenhua Dong
Ruiming Tang
OTCML
220
53
0
27 Oct 2023
On the Convergence of CART under Sufficient Impurity Decrease Condition
On the Convergence of CART under Sufficient Impurity Decrease ConditionNeural Information Processing Systems (NeurIPS), 2023
Rahul Mazumder
Haoyue Wang
256
6
0
26 Oct 2023
CATE Lasso: Conditional Average Treatment Effect Estimation with
  High-Dimensional Linear Regression
CATE Lasso: Conditional Average Treatment Effect Estimation with High-Dimensional Linear Regression
Masahiro Kato
Masaaki Imaizumi
CML
302
2
0
25 Oct 2023
Causal Q-Aggregation for CATE Model Selection
Causal Q-Aggregation for CATE Model SelectionInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Hui Lan
Vasilis Syrgkanis
CML
416
5
0
25 Oct 2023
Transparency challenges in policy evaluation with causal machine
  learning -- improving usability and accountability
Transparency challenges in policy evaluation with causal machine learning -- improving usability and accountability
Patrick Rehill
Nicholas Biddle
CMLELM
255
9
0
20 Oct 2023
MMD-based Variable Importance for Distributional Random Forest
MMD-based Variable Importance for Distributional Random ForestInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Clément Bénard
Jeffrey Näf
Julie Josse
241
1
0
18 Oct 2023
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