VIBES is a software package which allows variational inference to be performed automatically on a Bayesian network (if the terms in italics don’t mean anything to you, read this tutorial before continuing). I created VIBES during my Ph.D. as an implementation of my Variational Message Passing algorithm.
Keywords for this software
References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- Liu, Han; Wang, Lie: TIGER: A tuning-insensitive approach for optimally estimating Gaussian graphical models (2017)
- Luttinen, Jaakko: BayesPy: variational Bayesian inference in Python (2016)
- Sizov, Sergej; Ens, Andreas: Eventfolk - automatische erkennung von ereignissen in sozialen medien (2010) ioport
- Titterington, D.M.: Bayesian methods for neural networks and related models (2004)