A Critical Look at the Consistency of Causal Estimation with Deep Latent Variable Models

Severi Rissanen, Pekka Marttinen

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

2 Citations (Scopus)
15 Downloads (Pure)

Abstract

Using deep latent variable models in causal inference has attracted considerable interest recently, but an essential open question is their ability to yield consistent causal estimates. While they have demonstrated promising results and theory exists on some simple model formulations, we also know that causal effects are not even identifiable in general with latent variables. We investigate this gap between theory and empirical results with analytical considerations and extensive experiments under multiple synthetic and real-world data sets, using the causal effect variational autoencoder (CEVAE) as a case study. While CEVAE seems to work reliably under some simple scenarios, it does not estimate the causal effect correctly with a misspecified latent variable or a complex data distribution, as opposed to its original motivation. Hence, our results show that more attention should be paid to ensuring the correctness of causal estimates with deep latent variable models.
Original languageEnglish
Title of host publicationAdvances in Neural Information Processing Systems 34 - 35th Conference on Neural Information Processing Systems, NeurIPS 2021
PublisherNeural Information Processing Systems Foundation
Pages4207-4217
Number of pages11
ISBN (Electronic)9781713845393
Publication statusPublished - 2021
MoE publication typeA4 Article in a conference publication
EventConference on Neural Information Processing Systems - Virtual, Online
Duration: 6 Dec 202114 Dec 2021
Conference number: 35
https://neurips.cc

Publication series

NameAdvances in Neural Information Processing Systems
PublisherNeural Information Processing Systems Foundation
Volume6
ISSN (Print)1049-5258

Conference

ConferenceConference on Neural Information Processing Systems
Abbreviated titleNeurIPS
CityVirtual, Online
Period06/12/202114/12/2021
Internet address

Keywords

  • causal infernce
  • consistency
  • deep latent variable model
  • variational autoencoder
  • cevae

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