BayesPy: Variational Bayesian Inference in Python']Python

被引:0
|
作者
Luttinen, Jaakko [1 ]
机构
[1] Aalto Univ, Dept Comp Sci, Espoo, Finland
关键词
variational Bayes; probabilistic programming; !text type='Python']Python[!/text;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
BayesPy is an open-source Python software package for performing variational Bayesian inference. It is based on the variational message passing framework and supports conjugate exponential family models. By removing the tedious task of implementing the variational Bayesian update equations, the user can construct models faster and in a less error-prone way. Simple syntax, flexible model construction and efficient inference make BayesPy suitable for both average and expert Bayesian users. It also supports some advanced methods such as stochastic and collapsed variational inference.
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页数:6
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