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Estimating Conditional Average Treatment Effects with Missing Treatment
  Information

Estimating Conditional Average Treatment Effects with Missing Treatment Information

2 March 2022
Milan Kuzmanovic
Tobias Hatt
Stefan Feuerriegel
    CML
ArXivPDFHTML

Papers citing "Estimating Conditional Average Treatment Effects with Missing Treatment Information"

16 / 16 papers shown
Title
Normalizing Flows for Interventional Density Estimation
Normalizing Flows for Interventional Density Estimation
Valentyn Melnychuk
Dennis Frauen
Stefan Feuerriegel
77
21
0
13 Sep 2022
Estimating individual treatment effects under unobserved confounding
  using binary instruments
Estimating individual treatment effects under unobserved confounding using binary instruments
Dennis Frauen
Stefan Feuerriegel
CML
71
20
0
17 Aug 2022
Combining Observational and Randomized Data for Estimating Heterogeneous
  Treatment Effects
Combining Observational and Randomized Data for Estimating Heterogeneous Treatment Effects
Tobias Hatt
Jeroen Berrevoets
Alicia Curth
Stefan Feuerriegel
M. Schaar
CML
76
31
0
25 Feb 2022
Deconfounding Temporal Autoencoder: Estimating Treatment Effects over
  Time Using Noisy Proxies
Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Time Using Noisy Proxies
Milan Kuzmanovic
Tobias Hatt
Stefan Feuerriegel
CML
81
22
0
06 Dec 2021
Generalizing Off-Policy Learning under Sample Selection Bias
Generalizing Off-Policy Learning under Sample Selection Bias
Tobias Hatt
D. Tschernutter
Stefan Feuerriegel
OffRL
61
18
0
02 Dec 2021
Sequential Deconfounding for Causal Inference with Unobserved
  Confounders
Sequential Deconfounding for Causal Inference with Unobserved Confounders
Tobias Hatt
Stefan Feuerriegel
CML
60
28
0
16 Apr 2021
Estimating Average Treatment Effects via Orthogonal Regularization
Estimating Average Treatment Effects via Orthogonal Regularization
Tobias Hatt
Stefan Feuerriegel
CML
186
36
0
21 Jan 2021
Counterfactual Representation Learning with Balancing Weights
Counterfactual Representation Learning with Balancing Weights
Serge Assaad
Shuxi Zeng
Chenyang Tao
Shounak Datta
Nikhil Mehta
Ricardo Henao
Fan Li
Lawrence Carin
CML
OOD
114
64
0
23 Oct 2020
Learning Weighted Representations for Generalization Across Designs
Learning Weighted Representations for Generalization Across Designs
Fredrik D. Johansson
Nathan Kallus
Uri Shalit
David Sontag
OOD
61
87
0
23 Feb 2018
Bayesian Inference of Individualized Treatment Effects using Multi-task
  Gaussian Processes
Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes
Ahmed Alaa
M. Schaar
CML
170
302
0
10 Apr 2017
Generalized Random Forests
Generalized Random Forests
Susan Athey
J. Tibshirani
Stefan Wager
314
1,358
0
05 Oct 2016
Learning Representations for Counterfactual Inference
Learning Representations for Counterfactual Inference
Fredrik D. Johansson
Uri Shalit
David Sontag
CML
OOD
BDL
280
729
0
12 May 2016
Fast and Accurate Deep Network Learning by Exponential Linear Units
  (ELUs)
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)
Djork-Arné Clevert
Thomas Unterthiner
Sepp Hochreiter
300
5,521
0
23 Nov 2015
Domain-Adversarial Training of Neural Networks
Domain-Adversarial Training of Neural Networks
Yaroslav Ganin
E. Ustinova
Hana Ajakan
Pascal Germain
Hugo Larochelle
François Laviolette
M. Marchand
Victor Lempitsky
GAN
OOD
372
9,486
0
28 May 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.8K
150,039
0
22 Dec 2014
Representation Learning: A Review and New Perspectives
Representation Learning: A Review and New Perspectives
Yoshua Bengio
Aaron Courville
Pascal Vincent
OOD
SSL
256
12,435
0
24 Jun 2012
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