Static posterior inference of Bayesian probabilistic programming via polynomial solving
In Bayesian probabilistic programming, a central problem is to estimate the normalised posterior distribution (NPD) of a probabilistic program with conditioning via score (a.k.a. observe) statements. Most previous approaches address this problem by Markov Chain Monte Carlo and variational inference,...
Main Authors: | Wang, Peixin, Yang, Tengshun, Fu, Hongfei, Li, Guanyan, Ong, Luke C. H. |
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Other Authors: | College of Computing and Data Science |
Format: | Journal Article |
Language: | English |
Published: |
2024
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/178970 |
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