Article

Faithful and Diverse Subgraph as Explanation for Large Probabilistic Graphical Models

2025-09-25

Abstract excerpt

<title>Abstract</title> <p>Probabilistic graphical models, capturing dependencies among random variables , have proven their capability in many practical tasks. However, their opaque inference mechanisms prevent broader applications. Unlike explaining deep neural networks, the explainability challenges in graphical models stem from recursive and extensive dependencies coupled with intricate inference processes. T...

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Literature Corpus work: ed55430b-94b2-5c0e-aadc-2b57105354ed
DOI: 10.21203/rs.3.rs-7397829/v1

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