Notebooks about Bayesian methods for machine learning
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Updated
Jul 12, 2026 - Jupyter Notebook
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Notebooks about Bayesian methods for machine learning
machine-learning bayesian-methods gaussian-processes bayesian-optimization bayesian-machine-learning variational-autoencoder
Python package for Bayesian Machine Learning with scikit-learn API
A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation
deep-neural-networks deep-learning tensorflow bayesian-inference gaussian-processes bayesian-machine-learning
Code for "A-NICE-MC: Adversarial Training for MCMC"
tensorflow markov-chain generative-adversarial-network neural-networks tensorflow-experiments bayesian-inference markov-chain-monte-carlo bayesian-machine-learning generative-models
Stochastic tree ensembles (BART / XBART) for supervised learning and causal inference
machine-learning bayesian-methods bart decision-trees bayesian-machine-learning probabilistic-models gradient-boosted-trees tree-ensembles
Bayesian additive regression trees (BART) for regression, classification, uncertainty quantification, and variable selection in R, with optional GPU acceleration.
machine-learning r cross-validation regression variable-selection classification bart gpu-acceleration ensemble-learning r-package decision-trees mcmc uncertainty-quantification bayesian-statistics bayesian-machine-learning bayesian-nonparametrics interpretable-machine-learning bayesian-additive-regression-trees posterior-inference partial-dependence
This contains a number of IP[y]: Notebooks that hopefully give a light to areas of bayesian machine learning.
machine-learning ipython-notebook bayesian-inference kernel-methods gaussian-processes bayesian-machine-learning
Hyperdimensional computing in JAX, with statistical guarantees.
BayesianNonparametrics in julia
julia bayesian-methods bayesian-machine-learning bayesian-nonparametric-models dirichlet-process-mixtures
BayesML: your first library for Bayesian machine learning
machine-learning statistics bayesian-inference variational-inference bayesian-statistics bayesian-machine-learning bayesian-decision-theory
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.
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
Bayesian Actor-Critic with Neural Networks. Developing an OpenAI Gym toolkit for Bayesian AC reinforcement learning.
reinforcement-learning gym bayesian-optimization bayesian-machine-learning continuous-control actor-critic model-free-rl bayesian-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.
deep-learning bayesian-inference variational-inference bayesian-machine-learning pyro bayesian-neural-networks tensorflow-probability tensorflow-2 probabilistic-deep-learning probabilistic-modelling
Implementation of Linear Models for Regression and Classification from scratch using Python & Numpy.
machine-learning numpy regression python3 supervised-learning classification bayesian-machine-learning generalized-linear-models ml-from-scratch
AI-enabled lithium carbonate production with integrated CO2 capture, boosting and optimizing sustainable Li-ion battery production.
sustainability ai active-learning bayesian-machine-learning co2-emissions lithium-ion-batteries high-throughput-experimentation lithium-production co2-capture sustainable-battery-production
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