Python code for "Probabilistic Machine learning" book by Kevin Murphy

Fully and Partially Bayesian Neural Nets

Course materials of "Bayesian Modelling and Probabilistic Programming with Numpyro, and Deep Generative Surrogates for Epidemiology"

A multiverse of Prophet models for timeseries

Bayesian Learning and Neural Networks (jupyter book sources)

Estimating time trees from very large phylogenies

The missing layers package for Bayesian inference

Efficient library for spectral analysis in high-energy astrophysics.

Bayesian Ecological Modeling in Python

Probabilistic deep learning using JAX

JAX Tutorial notebooks : basics, crash & tips, usage of optax/JaxOptim/Numpyro

My implementation of John K. Kruschke's Doing Bayesian Data Analysis 2nd edition using Python and Numpyro.

Scalable Bayesian Modelling: A comparison

Tutorials for the 2022 IAIFI Summer School, covering (deep) probabilistic programming with Jax and NumPyro.

Summary notebooks using derivative gaussian processes with tinygp. We implement a 2D derivative gaussian process and successfully use derivatives to regularize SVI fits with a gaussian process model..

Hierarchical Bayesian estimation of MEP recruitment curves

Mixture regression models for NumPyro.

Very easy Bayesian regression.

Bayesian inference using sparse gaussian processes from tinygp. Examples include 1D and 2D implementation.

Oxford MSc thesis. variational autoencoder combined with graph convolutional networks for learning locally-aware spatial prior distributions