bayesian-nonparametrics

Code for "Hierarchical Dirichlet-Hawkes process: generative model and inference algorithm", WWW 2017

ACM CHIL 2020: "Survival Cluster Analysis"

An R Package for Bayesian Nonparametric Clustering. We plan to implement several models.

Implementation of the BNPool layer and code to reproduce the experiments in "Bayesian Nonparametric GNNs for graph pooling and clustering".

Infinite Mixtures of Infinite Factor Analysers

Bayesian Structure Adaptation for Continual Learning. A non-parametric Bayesian approach on continual learning that learns the sparse deep substructure for each task by selecting weights to be used by the deep neural network.

Coordinate Ascent Variational Inference for Dirichlet Process Mixtures of Gaussians

The code for DirBN in NeurIPS 2018

A Julia Package for Bayesian Nonparametric Analysis for Machine Learning

Supplementary code to the paper "Computational methods for Bayesian semiparametric Item Response Theory models"

Project for the Bayesian Statistics course of the MSc in Mathematical Engineering @ Polimi (A.Y. 2022-2023).

Reproducibility materials for "Bayesian Semiparametric Mixed Effects Markov Models with Application to Vocalization Syntax" by Abhra Sarkar, Jonathan Chabout, Joshua Jones Macopson, Erich D. Jarvis & David B. Dunson

Supporting Information for "Bayesian nonparametric analysis for the detection of spikes in noisy calcium imaging data"

Bayesian nonparametric clustering of functional data.

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

Apache PredictionIO Template: Bayesian Nonparametric Chinese Restaurant Process Clustering

Bayesian Nonparametrics

Bayesian non-parametrics for out of distribution detection

Theory and literature companion for Bayesian semiparametric item response modelling: identification, reliability, Dirichlet process mixture priors, and goal-specific posterior summaries. Quarto web monograph.