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Rothschild Lecture: Hamiltonian Monte Carlo and geometric integration

Presented by: 
Chus Sanz-Serna Universidad Carlos III de Madrid, Universidad de Valladolid
Date: 
Friday 6th December 2019 - 16:00 to 17:00
Venue: 
INI Seminar Room 1
Abstract: 
Many application fields require samples from an arbitrary probability distribution. Hamiltonian Monte Carlo is a sampling algorithm that originated in the physics literature and has later gained much popularity among statisticians. This is a talk addressed to a general audience, where I will describe the algorithm and some of its applications. The exposition requires basic ideas from different fields, from statistical physics to geometric integration of differential equations and from Bayesian statistics to Hamiltonian dynamics and I will provide the necessary background, albeit superficially.




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Presentation Material: 
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons