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