exact-inference

Bayesian Inference

FAIKR MOD3 project

Implementation of exact inference on Bayesian Network using Junction Trees in Python

This project implements both exact and approximate inference techniques for Bayesian Networks using enumeration and rejection sampling, respectively. It processes Bayesian Network structures in XMLBIF format, accepting command-line inputs to compute the posterior distribution of a query variable given observed evidence.

Fast exact finite-sample back-testing for Value-at-Risk (VaR) models in R.

Implementation of Prior, Rejection, Likelihood and Gibbs Sampling

A from-scratch exact Bayesian-network inference engine (Enumeration-Ask, no probabilistic-reasoning library) in C#, wrapped in a Blazor WebAssembly + ASP.NET Core app for building networks and querying them in the browser