GitHub

Active-Inference-Tutorial-Scripts

Step_by_Step_AI_Guide.m: This is the main tutorial script. It illustrates how to build a partially observable Markov decision process (POMDP) model within the active inference framework, using a ...
IEEE

Tutorial and Survey on Probabilistic Graphical Model and Variational Inference in Deep Reinforcement Learning

Abstract: Aiming at a comprehensive and concise tutorial survey, recap of variational inference and reinforcement learning with Probabilistic Graphical Models are given with detailed derivations.
GitHub

FaizSayyid/approximate-bayesian-inference-tutorial

: The posterior; the probability of the hypothesis (e.g. that a parameter has a certain value) given the data: The likelihood of observing/generating the data given the hypothesis: The prior ...
IEEE

Distributed Variational Inference for Online Supervised Learning

Abstract: This article introduces a scalable distributed probabilistic inference algorithm for intelligent sensor networks, tackling challenges of continuous variables, intractable posteriors, and ...