bayesian-machine-learning

Notebooks about Bayesian methods for machine learning

Python package for Bayesian Machine Learning with scikit-learn API

A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation

Code for "A-NICE-MC: Adversarial Training for MCMC"

Stochastic tree ensembles (BART / XBART) for supervised learning and causal inference

Bayesian additive regression trees (BART) for regression, classification, uncertainty quantification, and variable selection in R, with optional GPU acceleration.

This contains a number of IP[y]: Notebooks that hopefully give a light to areas of bayesian machine learning.

Hyperdimensional computing in JAX, with statistical guarantees.

BayesianNonparametrics in julia

MLSS-2026 Melbourne Bert's lectures

This is a GitHub repository for our Bayeisan Machine Learning textbook, which includes the PDF for the book and accompanying Python notebooks.

BayesML: your first library for Bayesian machine learning

A fast combinatorial tool that tests your password against real-world scenarios utilizing a novel Bayesian Machine Learning (BML) approach.

Key words: Bayesian analysis, Probabilistic programming, Data analysis, Bayesian machine learning... Using Python with its library PyMC3, pandas...

Bayesian methods for machine learning course at CentraleSupélec

Efficient approximate Bayesian machine learning

Implementation of Linear Models for Regression and Classification from scratch using Python & Numpy.

Bayesian Actor-Critic with Neural Networks. Developing an OpenAI Gym toolkit for Bayesian AC reinforcement learning.

Exploration of TensorFlow-2 and TensorFlow probability to implement Bayesian Neural Networks, Normalizing flows, real NVPs and Autoencoders. Exploration of Bayesian Modelling and Variational Inference with Pyro.

AI-enabled lithium carbonate production with integrated CO2 capture, boosting and optimizing sustainable Li-ion battery production.