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Modified Causal Forests for Estimating Heterogeneous Causal Effects
v1v2 (latest)

Modified Causal Forests for Estimating Heterogeneous Causal Effects

22 December 2018
M. Lechner
    CML
ArXiv (abs)PDFHTML

Papers citing "Modified Causal Forests for Estimating Heterogeneous Causal Effects"

6 / 6 papers shown
Title
Double Machine Learning for Static Panel Models with Fixed Effects
Double Machine Learning for Static Panel Models with Fixed Effects
Paul Clarke
Annalivia Polselli
171
3
0
03 Jan 2025
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 Modeling
Zexu Sun
Xu Chen
60
3
0
24 Jan 2024
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
81
4
0
20 Oct 2023
Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit
  Performance
Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance
Gabriel Okasa
CML
53
6
0
30 Jan 2022
Priority to unemployed immigrants? A causal machine learning evaluation
  of training in Belgium
Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium
Bart Cockx
Michael Lechner
Joost Boolens
CML
71
110
0
30 Dec 2019
Response Transformation and Profit Decomposition for Revenue Uplift
  Modeling
Response Transformation and Profit Decomposition for Revenue Uplift Modeling
R. M. Gubela
Stefan Lessmann
S. Jaroszewicz
OffRL
62
51
0
20 Nov 2019
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