19 citations · 19 across the 2 of their papers we have counts for
2 papers
stat.CO2016
Langevin Incremental Mixture Importance Sampling
Matteo Fasiolo, Flávio Eler de Melo, Simon Maskell
This work proposes a novel method through which local information about the target density can be used to construct an efficient importance sampler. The backbone of the proposed me…
stat.ME2015★ 19 cited
Stochastic Particle Flow for Nonlinear High-Dimensional Filtering Problems
Flávio Eler De Melo, Simon Maskell, Matteo Fasiolo +1
A series of novel filters for probabilistic inference that propose an alternative way of performing Bayesian updates, called particle flow filters, have been attracting recent inte…