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2101.10943
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Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
26 January 2021
Alicia Curth
M. Schaar
CML
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Papers citing
"Nonparametric Estimation of Heterogeneous Treatment Effects: From Theory to Learning Algorithms"
18 / 118 papers shown
Neural Score Matching for High-Dimensional Causal Inference
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Oscar Clivio
Fabian Falck
B. Lehmann
George Deligiannidis
Chris Holmes
CML
222
9
0
01 Mar 2022
Combining Observational and Randomized Data for Estimating Heterogeneous Treatment Effects
Tobias Hatt
Jeroen Berrevoets
Alicia Curth
Stefan Feuerriegel
M. Schaar
CML
293
36
0
25 Feb 2022
A Free Lunch with Influence Functions? Improving Neural Network Estimates with Concepts from Semiparametric Statistics
M. Vowels
S. Akbari
Necati Cihan Camgöz
Richard Bowden
246
4
0
18 Feb 2022
Generalized Causal Tree for Uplift Modeling
BigData Congress [Services Society] (BSS), 2022
Preetam Nandy
Xiufan Yu
Wanjun Liu
Ye Tu
Kinjal Basu
S. Chatterjee
CML
236
7
0
04 Feb 2022
To Impute or not to Impute? Missing Data in Treatment Effect Estimation
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Jeroen Berrevoets
F. Imrie
T. Kyono
James Jordon
M. Schaar
336
21
0
04 Feb 2022
Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation
Yi-Fan Zhang
Hanlin Zhang
Zachary Chase Lipton
Li Erran Li
Eric P. Xing
OODD
381
35
0
02 Feb 2022
Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance
Gabriel Okasa
CML
214
12
0
30 Jan 2022
Multi-treatment Effect Estimation from Biomedical Data
Raquel Y. S. Aoki
Yizhou Chen
M. Ester
224
0
0
14 Dec 2021
Causal Effect Variational Autoencoder with Uniform Treatment
Daniel Jiwoong Im
Kyunghyun Cho
N. Razavian
OOD
CML
BDL
197
10
0
16 Nov 2021
SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data
Alicia Curth
Changhee Lee
M. Schaar
CML
207
33
0
26 Oct 2021
Covariate Balancing Methods for Randomized Controlled Trials Are Not Adversarially Robust
Hossein Babaei
Sina Alemohammad
Richard Baraniuk
334
0
0
25 Oct 2021
Heterogeneous Treatment Effect Estimation using machine learning for Healthcare application: tutorial and benchmark
Journal of Biomedical Informatics (JBI), 2021
Yaobin Ling
Pulakesh Upadhyaya
Luyao Chen
Xiaoqian Jiang
Yejin Kim
CML
433
25
0
27 Sep 2021
Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal Effects
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Yao Zhang
Jeroen Berrevoets
M. Schaar
CML
303
6
0
06 Aug 2021
Doing Great at Estimating CATE? On the Neglected Assumptions in Benchmark Comparisons of Treatment Effect Estimators
Alicia Curth
M. Schaar
CML
144
7
0
28 Jul 2021
On Inductive Biases for Heterogeneous Treatment Effect Estimation
Neural Information Processing Systems (NeurIPS), 2021
Alicia Curth
M. Schaar
CML
355
100
0
07 Jun 2021
Causal Effect Inference for Structured Treatments
Neural Information Processing Systems (NeurIPS), 2021
Jean Kaddour
Yuchen Zhu
Qi Liu
Matt J. Kusner
Ricardo M. A. Silva
CML
497
53
0
03 Jun 2021
Sequential Deconfounding for Causal Inference with Unobserved Confounders
CLEaR (CLEaR), 2021
Tobias Hatt
Stefan Feuerriegel
CML
331
30
0
16 Apr 2021
Generalization Bounds and Representation Learning for Estimation of Potential Outcomes and Causal Effects
Journal of machine learning research (JMLR), 2020
Fredrik D. Johansson
Uri Shalit
Nathan Kallus
David Sontag
CML
OOD
439
120
0
21 Jan 2020
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