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

Bayesian Learning and Neural Networks (jupyter book sources)

A multiverse of Prophet models for timeseries

Estimating time trees from very large phylogenies

Probabilistic deep learning using JAX

Efficient library for spectral analysis in high-energy astrophysics.

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..

Very easy Bayesian regression.

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

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

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

Mixture regression models for NumPyro.

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.

Hierarchical Bayesian estimation of MEP recruitment curves

my collection of notebooks from issues, pull requests, forum