Projects per year
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 language | English |
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Title of host publication | Advances in Neural Information Processing Systems 34 - 35th Conference on Neural Information Processing Systems, NeurIPS 2021 |
Publisher | Neural Information Processing Systems Foundation |
Pages | 4207-4217 |
Number of pages | 11 |
ISBN (Electronic) | 9781713845393 |
Publication status | Published - 2021 |
MoE publication type | A4 Conference publication |
Event | Conference on Neural Information Processing Systems - Virtual, Online Duration: 6 Dec 2021 → 14 Dec 2021 Conference number: 35 https://neurips.cc |
Publication series
Name | Advances in Neural Information Processing Systems |
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Publisher | Neural Information Processing Systems Foundation |
Volume | 6 |
ISSN (Print) | 1049-5258 |
Conference
Conference | Conference on Neural Information Processing Systems |
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Abbreviated title | NeurIPS |
City | Virtual, Online |
Period | 06/12/2021 → 14/12/2021 |
Internet address |
Keywords
- causal infernce
- consistency
- deep latent variable model
- variational autoencoder
- cevae
Fingerprint
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INTERVENE: International consortium for integrative genomics prediction
Kaski, S. (Principal investigator)
01/01/2021 → 31/12/2025
Project: EU: Framework programmes funding
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DATALIT: Data Literacy for Responsible Decision-Making
Marttinen, P. (Principal investigator)
01/10/2020 → 30/09/2023
Project: Academy of Finland: Strategic research funding
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eMOM: CleverHealth Network: eMOM GDM -Project
Marttinen, P. (Principal investigator)
05/02/2018 → 31/01/2023
Project: Business Finland: Other research funding
Equipment
Activities
- 2 Invited academic talk
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A Critical Look at the Consistency of Causal Estimation with Deep Latent Variable Models
Rissanen, S. (Speaker)
18 Oct 2021Activity: Talk or presentation types › Invited academic talk
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A Critical Look at the Consistency of Causal Estimation with Deep Latent Variable Models
Rissanen, S. (Speaker)
8 Dec 2021Activity: Talk or presentation types › Invited academic talk