Derivation of the Variational Bayes Equations
June 20, 2019 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Alianna J. Maren
arXiv ID
1906.08804
Category
cs.NE: Neural & Evolutionary
Cross-listed
q-bio.NC
Citations
4
Venue
arXiv.org
Last Checked
4 months ago
Abstract
The derivation of key equations for the variational Bayes approach is well-known in certain circles. However, translating the fundamental derivations (e.g., as found in Beal's work) to Friston's notation is somewhat delicate. Further, the notion of using variational Bayes in the context of a system with a Markov blanket requires special attention. This Technical Report presents the derivation in detail. It further illustrates how the variational Bayes method provides a framework for a new computational engine, incorporating the 2-D cluster variation method (CVM), which provides a necessary free energy equation that can be minimized across both the external and representational systems' states, respectively.
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