Code for "Hierarchical Dirichlet-Hawkes process: generative model and inference algorithm", WWW 2017
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Updated
Dec 4, 2018 - Python
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.
The code for DirBN in NeurIPS 2018
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.
Infinite Mixtures of Infinite Factor Analysers
A Julia Package for Bayesian Nonparametric Analysis for Machine Learning
Supplementary code to the paper "Computational methods for Bayesian semiparametric Item Response Theory models"
This repository captures code developed during my PhD at the University of Bath and includes the implementation of the DP-GP-LVM model.
Supporting Information for "Bayesian nonparametric analysis for the detection of spikes in noisy calcium imaging data"
Coordinate Ascent Variational Inference for Dirichlet Process Mixtures of Gaussians
Project for the Bayesian Statistics course of the MSc in Mathematical Engineering @ Polimi (A.Y. 2022-2023).
Apache PredictionIO Template: Bayesian Nonparametric Chinese Restaurant Process Clustering
Bayesian Nonparametrics
Bayesian nonparametric clustering of functional data.
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
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
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