Tractable uncertainty for structure learning

Bayesian structure learning allows one to capture uncertainty over the causal directed acyclic graph (DAG) responsible for generating given data. In this work, we present Tractable Uncertainty for STructure learning (TRUST), a framework for approximate posterior inference that relies on probabilisti...

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Bibliografski detalji
Glavni autori: Wang, B, Wicker, M, Kwiatkowska, M
Format: Conference item
Jezik:English
Izdano: Journal of Machine Learning Research 2022