Hamiltonian Monte Carlo

I-priors in Bayesian Variable Selection: From Reproducing Kernel Hilbert Spaces to Hamiltonian Monte Carlo

I-priors are a class of objective priors for regression functions which makes use of its Fisher information in a function space framework. Currently, I am exploring the use of I-priors in Bayesian variable selection. My talk is a collection of ideas …

Hamiltonian Monte Carlo explainer

Shiny apps for explaining Hamiltonian Monte Carlo.