There are 3 repositories under bayesian-nonparametrics topic.
Code for "Hierarchical Dirichlet-Hawkes process: generative model and inference algorithm", WWW 2017
An R Package for Bayesian Nonparametric Clustering. We plan to implement several models.
ACM CHIL 2020: "Survival Cluster Analysis"
Implementation of the BNPool layer and code to reproduce the experiments in "Bayesian Nonparametric GNNs for graph pooling and clustering".
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.
The code for DirBN in NeurIPS 2018
Infinite Mixtures of Infinite Factor Analysers
Coordinate Ascent Variational Inference for Dirichlet Process Mixtures of Gaussians
A Julia Package for Bayesian Nonparametric Analysis for Machine Learning
Supplementary code to the paper "Computational methods for Bayesian semiparametric Item Response Theory models"
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
Project for the Bayesian Statistics course of the MSc in Mathematical Engineering @ Polimi (A.Y. 2022-2023).
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
Supporting Information for "Bayesian nonparametric analysis for the detection of spikes in noisy calcium imaging data"
Bayesian nonparametric clustering of functional data.
Bayesian Nonparametrics
A Julia interface for Dirichlet process mixture (DPM) models using Neal's algorithm 3.
Functional Spatial Temporal Aggregated Dirichlet Process Predictors
Repository for my research project on Inverse Contextual Bandits