Modelling and Inference with Conditional Gaussian Probabilistic Decision Graphs*
Probabilistic decision graphs (PDGs) are probabilistic graphical models that represent a factorisation of a discrete joint probability distribution using a “decision graph”-like structure over local marginal parameters. The structure of a PDG enables the model to capture some context specific indepe...
| 主要な著者: | , , |
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| フォーマット: | info:eu-repo/semantics/article |
| 言語: | English |
| 出版事項: |
2017
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| 主題: | |
| オンライン･アクセス: | http://hdl.handle.net/10835/4891 https://doi.org/10.1016/j.ijar.2011.09.005 |