Gibbs sampler for the Hierarchical Latent Dirichlet Allocation topic model

A Python/C++ implementation of Bayesian Factorization Machines

Hierarchical, multi-label topic modelling with LDA

A Latent Dirichlet Allocation implementation in Python.

Visualization of Gibbs sampling for 2D Gaussian distribution

Code to perform multivariate linear regression using Gibbs sampling

Estimate the Deterministic Input, Noisy "And" Gate (DINA) cognitive diagnostic model parameters using the Gibbs sampler described by Culpepper (2015) <doi:10.3102/1076998615595403>.

matlab

glmdisc Python package: discretization, factor level grouping, interaction discovery for logistic regression

Generating samples from Ising model.

Bayesian trend filtering micro library. http://trendpy.readthedocs.io/en/latest/

Archaeological Synchronism

R implementation of the Dirichlet Process Gaussian Mixture Model (with MCMC)

Libary for SGPD (Sigmoidal Gaussian Process Density) inference

Approximate Bayesian inference for mixed effects models with heterogeneity

Localization of brain sources measured by EEG using 3 approaches: Gibbs sampler (Markov chain Monte Carlo algorithm), Minimum Norm Estimates (MNE) and Source Imaging based on Structured Sparsity (SISSY)

In the first semester of my MSc. studies, we developed a phyton version of the Gibbs Sampler and Metropolis-Hastings Algorithm from the scratch. We described our results and analysis in a report.

Implementation of a Gibbs-Metropolis sampling algorithm in CUDA

Package to do Bayesian inference with Gibbs sampler

Bayesian Regression Analyses from scratch - NBA data example