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

Bayesian Learning and Neural Networks (jupyter book sources)

Estimating time trees from very large phylogenies

An implementation of Prophet for hierarchical timeseries in numpyro.

Probabilistic deep learning using JAX

Scalable Bayesian Modelling: A comparison

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

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

Efficient library for spectral analysis in high-energy astrophysics.

Very easy Bayesian regression.

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..

Repo for course CSC2558: "Intelligent Adaptive Interventions" project in nonstationary contextual bandits.

Statistical rethinking by Richard McElreath. Learning notes, code port to PyMC (mainly for MCMC) v5 & Numpyro (mainly for `quap`).

Build, fit, and sample from cognitive models with JAX + NumPyro.

my collection of notebooks from issues, pull requests, forum

Mixture regression models for NumPyro.

A basic example to run ML code on SLURM (specifically Oxford's ARC systems) in a organised fashion

Bayesian Analysis in Python (2nd ed.) with Numpyro

Pretty, easy, flexible Bayesian estimation with data overlay