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Identifiable Energy-based Representations: An Application to Estimating
  Heterogeneous Causal Effects
v1v2v3 (latest)

Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal Effects

International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
6 August 2021
Yao Zhang
Jeroen Berrevoets
M. Schaar
    CML
ArXiv (abs)PDFHTML

Papers citing "Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal Effects"

3 / 3 papers shown
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
418
0
0
06 Nov 2023
Causal Machine Learning for Healthcare and Precision Medicine
Causal Machine Learning for Healthcare and Precision MedicineRoyal Society Open Science (RSOS), 2022
Pedro Sanchez
J. Voisey
Tian Xia
Hannah I. Watson
Alison Q. OÑeil
Sotirios A. Tsaftaris
OODCML
371
204
0
23 May 2022
To Impute or not to Impute? Missing Data in Treatment Effect Estimation
To Impute or not to Impute? Missing Data in Treatment Effect EstimationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Jeroen Berrevoets
F. Imrie
T. Kyono
James Jordon
M. Schaar
445
21
0
04 Feb 2022
1
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