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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 / No. 12: AAAI-21 Technical Tracks 12

Treatment Effect Estimation with Disentangled Latent Factors

February 1, 2023

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Authors

Weijia Zhang

University of South Australia


Lin Liu

University of South Australia


Jiuyong Li

University of South Australia


DOI:

10.1609/aaai.v35i12.17304


Abstract:

Much research has been devoted to the problem of estimating treatment effects from observational data; however, most methods assume that the observed variables only contain confounders, i.e., variables that affect both the treatment and the outcome. Unfortunately, this assumption is frequently violated in real-world applications, since some variables only affect the treatment but not the outcome, and vice versa. Moreover, in many cases only the proxy variables of the underlying confounding factors can be observed. In this work, we first show the importance of differentiating confounding factors from instrumental and risk factors for both average and conditional average treatment effect estimation, and then we propose a variational inference approach to simultaneously infer latent factors from the observed variables, disentangle the factors into three disjoint sets corresponding to the instrumental, confounding, and risk factors, and use the disentangled factors for treatment effect estimation. Experimental results demonstrate the effectiveness of the proposed method on a wide range of synthetic, benchmark, and real-world datasets.

Topics: AAAI

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HOW TO CITE:

Weijia Zhang||Lin Liu||Jiuyong Li Treatment Effect Estimation with Disentangled Latent Factors Proceedings of the AAAI Conference on Artificial Intelligence (2021) 10923-10930.

Weijia Zhang||Lin Liu||Jiuyong Li Treatment Effect Estimation with Disentangled Latent Factors AAAI 2021, 10923-10930.

Weijia Zhang||Lin Liu||Jiuyong Li (2021). Treatment Effect Estimation with Disentangled Latent Factors. Proceedings of the AAAI Conference on Artificial Intelligence, 10923-10930.

Weijia Zhang||Lin Liu||Jiuyong Li. Treatment Effect Estimation with Disentangled Latent Factors. Proceedings of the AAAI Conference on Artificial Intelligence 2021 p.10923-10930.

Weijia Zhang||Lin Liu||Jiuyong Li. 2021. Treatment Effect Estimation with Disentangled Latent Factors. "Proceedings of the AAAI Conference on Artificial Intelligence". 10923-10930.

Weijia Zhang||Lin Liu||Jiuyong Li. (2021) "Treatment Effect Estimation with Disentangled Latent Factors", Proceedings of the AAAI Conference on Artificial Intelligence, p.10923-10930

Weijia Zhang||Lin Liu||Jiuyong Li, "Treatment Effect Estimation with Disentangled Latent Factors", AAAI, p.10923-10930, 2021.

Weijia Zhang||Lin Liu||Jiuyong Li. "Treatment Effect Estimation with Disentangled Latent Factors". Proceedings of the AAAI Conference on Artificial Intelligence, 2021, p.10923-10930.

Weijia Zhang||Lin Liu||Jiuyong Li. "Treatment Effect Estimation with Disentangled Latent Factors". Proceedings of the AAAI Conference on Artificial Intelligence, (2021): 10923-10930.

Weijia Zhang||Lin Liu||Jiuyong Li. Treatment Effect Estimation with Disentangled Latent Factors. AAAI[Internet]. 2021[cited 2023]; 10923-10930.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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