Predicting Purchase Rates in Stationary Markets

This project was realized for the Bayesian Statistics course, held at Politecnico di Milano, A.Y. 2022/2023.

A demo of Dirichlet Distribution, Dirichlet Process and the Chinese Restaurant Process based GMM Clustering

Bayesian Overlapping Community Detector (DBOCD) in Dynamic Networks

Functional Spatial Temporal Aggregated Dirichlet Process Predictors

Implementation of Rasmussen's paper on The Infinite Gaussian Mixture Model

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

[ECCV'24] cDP-MIL: Robust Multiple Instance Learning via Cascaded Dirichlet Process

streaming field recording shuffler cross-platform and JACK audio

Source code for the CopRe R package

MATALAB code for "Clustering Curves Based on Change Point Analysis: A Nonparametric Bayesian Approach", Statistica Sinica

The code interface is written in R, and for the sake of speed, most parts are written in C++. However, no prerequisite knowledge for both languages is required to run the code. An R file called runInfHMM.R sources all needed functions to compile and run the code.

A Predictive View of Bayesian Clustering

It is about Chinese Restaurant Progress.

Non-parametric Bayesian Model

Code to work with Dirichlet processes and hierarchical Dirichlet processes and perform inference using MCMC.

This repository captures code developed during my PhD at the University of Bath and includes the implementation of the DP-GP-LVM model.

Probabilistic Models of Human and Machine Intelligence

Code for our UAI '20 paper "Scalable and Flexible Clustering of Grouped Data via Parallel and Distributed Sampling in Versatile Hierarchical Dirichlet Processes"