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Covariate-Balancing-Aware Interpretable Deep Learning models for
  Treatment Effect Estimation

Covariate-Balancing-Aware Interpretable Deep Learning models for Treatment Effect Estimation

7 March 2022
Kan Chen
Qishuo Yin
Q. Long
    CML
ArXivPDFHTML

Papers citing "Covariate-Balancing-Aware Interpretable Deep Learning models for Treatment Effect Estimation"

5 / 5 papers shown
Title
DISCRET: Synthesizing Faithful Explanations For Treatment Effect
  Estimation
DISCRET: Synthesizing Faithful Explanations For Treatment Effect Estimation
Yinjun Wu
Mayank Keoliya
Kan Chen
Neelay Velingker
Ziyang Li
E. Getzen
Qi Long
Mayur Naik
Ravi B. Parikh
Eric Wong
47
1
0
02 Jun 2024
NAISR: A 3D Neural Additive Model for Interpretable Shape Representation
NAISR: A 3D Neural Additive Model for Interpretable Shape Representation
Yining Jiao
C. Zdanski
Julia Kimbell
Andrew Prince
Cameron P Worden
...
Christopher Rutter
Benjamin Shields
William Dunn
Jisan Mahmud
Marc Niethammer
39
3
0
16 Mar 2023
Benchmarking Heterogeneous Treatment Effect Models through the Lens of
  Interpretability
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability
Jonathan Crabbé
Alicia Curth
Ioana Bica
M. Schaar
CML
22
16
0
16 Jun 2022
Causal Effect Inference for Structured Treatments
Causal Effect Inference for Structured Treatments
Jean Kaddour
Yuchen Zhu
Qi Liu
Matt J. Kusner
Ricardo M. A. Silva
CML
174
50
0
03 Jun 2021
Learning Representations for Counterfactual Inference
Learning Representations for Counterfactual Inference
Fredrik D. Johansson
Uri Shalit
David Sontag
CML
OOD
BDL
229
719
0
12 May 2016
1