141 citations · 597 across the 22 of their papers we have counts for
4 papers · 1 filter
Cooperative Parallel Particle Filters for online model selection and applications to Urban Mobility
Luca Martino, Jesse Read, Victor Elvira +1
We design a sequential Monte Carlo scheme for the dual purpose of Bayesian inference and model selection. We consider the application context of urban mobility, where several modal…
Improved Adaptive Rejection Metropolis Sampling Algorithms
Luca Martino, Jesse Read, David Luengo
Markov Chain Monte Carlo (MCMC) methods, such as the Metropolis-Hastings (MH) algorithm, are widely used for Bayesian inference. One of the most important issues for any MCMC metho…
On the flexibility of the design of Multiple Try Metropolis schemes
Luca Martino, Jesse Read
The Multiple Try Metropolis (MTM) method is a generalization of the classical Metropolis-Hastings algorithm in which the next state of the chain is chosen among a set of samples, a…
A multi-point Metropolis scheme with generic weight functions
Luca Martino, Victor Pascual Del Olmo, Jesse Read
The multi-point Metropolis algorithm is an advanced MCMC technique based on drawing several correlated samples at each step and choosing one of them according to some normalized we…