output
20152020
most citedGeneralized Multiple Importance Sampling

144 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing 2016Show all

2 papers · 1 filter

stat.CO2016★ 34 cited

The Recycling Gibbs Sampler for Efficient Learning

Luca Martino, Victor Elvira, Gustau Camps-Valls

Monte Carlo methods are essential tools for Bayesian inference. Gibbs sampling is a well-known Markov chain Monte Carlo (MCMC) algorithm, extensively used in signal processing, mac…

stat.CO2016★ 23 cited

Independent Resampling Sequential Monte Carlo Algorithms

Roland Lamberti, Yohan Petetin, François Desbouvries +1

Sequential Monte Carlo algorithms, or Particle Filters, are Bayesian filtering algorithms which propagate in time a discrete and random approximation of the a posteriori distributi…