A NumPyro implementation of Bayesian Synthetic Control Methods.

A NumPyro implementation of Bayesian estimation supersedes the t-test.

A gentle introduction to variational inference applied to Bayesian logistic regressions with accompanying PyTorch implementation.

A short post on scoring rules and their connection to a divergence metric.

Let’s derive the evidence lower bound used in variational inference using Jensen’s inequality and the Kullback-Leibler divergence.

A GP implementation using Jax that shows kernel computation, conditioning of Gaussian distributions, parameter transformations, and gradient-based optimisation.