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Stochastic Tree Ensembles for Estimating Heterogeneous Effects

Stochastic Tree Ensembles for Estimating Heterogeneous Effects

15 September 2022
Nikolay M. Krantsevich
Jingyu He
P. R. Hahn
    CML
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Papers citing "Stochastic Tree Ensembles for Estimating Heterogeneous Effects"

5 / 5 papers shown
Title
Forests for Differences: Robust Causal Inference Beyond Parametric DiD
Forests for Differences: Robust Causal Inference Beyond Parametric DiD
Hugo Gobato Souto
Francisco Louzada Neto
11
0
0
14 May 2025
Bayesian Causal Forests for Longitudinal Data: Assessing the Impact of
  Part-Time Work on Growth in High School Mathematics Achievement
Bayesian Causal Forests for Longitudinal Data: Assessing the Impact of Part-Time Work on Growth in High School Mathematics Achievement
Nathan McJames
Ann O'Shea
Andrew C. Parnell
33
0
0
16 Jul 2024
Deep Learning for Causal Inference: A Comparison of Architectures for
  Heterogeneous Treatment Effect Estimation
Deep Learning for Causal Inference: A Comparison of Architectures for Heterogeneous Treatment Effect Estimation
Demetrios Papakostas
Andrew Herren
P. R. Hahn
Francisco Castillo
CML
BDL
24
0
0
06 May 2024
Feature selection in stratification estimators of causal effects:
  lessons from potential outcomes, causal diagrams, and structural equations
Feature selection in stratification estimators of causal effects: lessons from potential outcomes, causal diagrams, and structural equations
P. R. Hahn
Andrew Herren
CML
21
3
0
23 Sep 2022
Local Gaussian process extrapolation for BART models with applications
  to causal inference
Local Gaussian process extrapolation for BART models with applications to causal inference
Meijia Wang
Jingyu He
P. R. Hahn
18
11
0
23 Apr 2022
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