An Introduction to Hamiltonian Monte Carlo Method for Sampling
@article{Vishnoi2021AnIT, title={An Introduction to Hamiltonian Monte Carlo Method for Sampling}, author={Nisheeth K. Vishnoi}, journal={ArXiv}, year={2021}, volume={abs/2108.12107} }
The goal of this article is to introduce the Hamiltonian Monte Carlo method – a Hamiltonian dynamics inspired algorithm for sampling from a Gibbs density π(x) ∝ e−f(x). We focus on the “idealized” case, where one can compute continuous trajectories exactly. We show that idealized HMC preserves π and we establish its convergence when f is strongly convex and smooth.
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