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News/Reconsidering Dependency Networks from an Information Geometry Perspective
arxiv
PublishedApril 2, 2026 at 4:00 AM
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Reconsidering Dependency Networks from an Information Geometry Perspective

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arXiv:2604.01117v1 Announce Type: new Abstract: Dependency networks (Heckerman et al., 2000) provide a flexible framework for modeling complex systems with many variables by combining independently learned local conditional distributions through pseudo-Gibbs sampling. Despite their computational adv

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