Scalable Variational Causal Discovery Unconstrained by Acyclicity Article Swipe
Nu Hoang
,
Bao Duong
,
Thin Nguyen
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3233/faia240801
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3233/faia240801
Bayesian causal discovery offers the power to quantify epistemic uncertainties among a broad range of structurally diverse causal theories potentially explaining the data, represented in forms of directed acyclic graphs (DAGs). However, existing methods struggle with efficient DAG sampling due to the complex acyclicity constraint. In this study, we propose a scalable Bayesian approach to effectively learn the posterior distribution over causal graphs given observational data thanks to the ability to generate DAGs without explicitly enforcing acyclicity. Specifically, we introduce a novel differentiable DAG sampling method that can generate a valid acyclic causal graph by mapping an unconstrained distribution of implicit topological orders to a distribution over DAGs. Given this efficient DAG sampling scheme, we are able to model the posterior distribution over causal graphs using a simple variational distribution over a continuous domain, which can be learned via the variational inference framework. Extensive empirical experiments on both simulated and real datasets demonstrate the superior performance of the proposed model compared to several state-of-the-art baselines.
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Metadata
- Type
- book-chapter
- Language
- en
- Landing Page
- https://doi.org/10.3233/faia240801
- https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240801
- OA Status
- hybrid
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4403518083
All OpenAlex metadata
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https://openalex.org/W4403518083Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3233/faia240801Digital Object Identifier
- Title
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Scalable Variational Causal Discovery Unconstrained by AcyclicityWork title
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book-chapterOpenAlex work type
- Language
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enPrimary language
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2024Year of publication
- Publication date
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2024-10-16Full publication date if available
- Authors
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Nu Hoang, Bao Duong, Thin NguyenList of authors in order
- Landing page
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https://doi.org/10.3233/faia240801Publisher landing page
- PDF URL
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https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240801Direct link to full text PDF
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA240801Direct OA link when available
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Scalability, Computer science, Theoretical computer science, DatabaseTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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