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

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

Bayesian Learning and Neural Networks (jupyter book sources)

A multiverse of Prophet models for timeseries

Estimating time trees from very large phylogenies

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

Probabilistic deep learning using JAX

Efficient library for spectral analysis in high-energy astrophysics.

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`).

Hierarchical Bayesian estimation of MEP recruitment curves

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