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...
| Main Authors: | , , |
|---|---|
| 格式: | Conference item |
| 语言: | English |
| 出版: |
Journal of Machine Learning Research
2022
|