Sanz Serna, Jesús María
Royal Academy of Sciences of Spain and Carlos III University of Madrid
Academician and former President of the Royal Academy of Sciences of Spain and Applied Mathematics Professor
Address
Carlos III University of Madrid Academic
Department: Mathematics - 2.2D31 - Sabatini (Leganés)
Email: jesanzs@math.uc3m.es - jesusmaria.sanz@uc3m.es
Phone: 916 249 166
Research Interests
The Hamiltonian or Hybrid Monte Carlo method
In many situations one requires to numerically generate samples of a given probability distribution in Rd; Bayesian statistics is a field where those situations arise constantly. Markov Chain Monte Carlo (MCMC) methods make it possible to obtain those samples even if d is large. HMC (Hybrid or Hamiltonian Monte Carlo) algorithms are widely used MCMC samplers which often outperform alternative techniques. In HMC each sample is obtained by integrating numerically a Hamiltonian system of differential equations with d degrees of freedom; there is then a clear connection between HMC and all my work on numerical Hamiltonian problems (to be completed).
See also
