Notebooks about Bayesian methods for machine learning
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Updated
Mar 6, 2024 - Jupyter Notebook
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"
This contains a number of IP[y]: Notebooks that hopefully give a light to areas of bayesian machine learning.
BayesianNonparametrics in julia
This is a GitHub repository for our Bayeisan Machine Learning textbook, which includes the PDF for the book and accompanying Python notebooks.
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
Bayesian Actor-Critic with Neural Networks. Developing an OpenAI Gym toolkit for Bayesian AC reinforcement learning.
Efficient approximate Bayesian machine learning
Library for Bayesian machine 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.
A Bayesian approach to predictive uncertainty in chemotherapy patients at risk of acute care utilization
Exercises on Bayesian linear regression, Gaussian Processes, Metropolis-Hastings Inference for Bayesian Logistic Regression, K-means and Probabilistic PCA. Made at Institut EURECOM (FR)
Assignment code for Bayesian ML course on Coursera
Platform for automatic processing of (aq-tngapms) Air Quality using TNGAPMS
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