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.
翻译:变式贝雅斯方法的关键方程式的推算在某些圈子中是众所周知的。然而,将基本推算(例如Beal的工作发现)转换为弗里斯顿的符号有些微妙。此外,在配有马尔科夫毯子的系统中使用变式贝雅斯的概念需要特别注意。本技术报告详细介绍了这种推算。它进一步说明了变式贝雅斯方法如何为新的计算引擎提供一个框架,其中包括2-D集束变换方法(CVM),该方法提供了必要的自由能源方程式,可以分别在外部和代表系统各州加以最小化。