23 citations · 44 across the 5 of their papers we have counts for
6 papers
Classifier Weighted Mixture models
Elouan Argouarc'h, François Desbouvries, Eric Barat +2
This paper proposes an extension of standard mixture stochastic models, by replacing the constant mixture weights with functional weights defined using a classifier. Classifier Wei…
Binary classification based Monte Carlo simulation
Elouan Argouarc'h, François Desbouvries
Acceptance-rejection (AR), Independent Metropolis Hastings (IMH) or importance sampling (IS) Monte Carlo (MC) simulation algorithms all involve computing ratios of probability dens…
Expressivity of Hidden Markov Chains vs. Recurrent Neural Networks from a system theoretic viewpoint
François Desbouvries, Yohan Petetin, Achille Salaün
Hidden Markov Chains (HMC) and Recurrent Neural Networks (RNN) are two well known tools for predicting time series. Even though these solutions were developed independently in dist…
Semi-independent resampling for particle filtering
Roland Lamberti, Yohan Petetin, François Desbouvries +1
Among Sequential Monte Carlo (SMC) methods,Sampling Importance Resampling (SIR) algorithms are based on Importance Sampling (IS) and on some resampling-based)rejuvenation algorithm…
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…
A class of fast exact Bayesian filters in dynamical models with jumps
Yohan Petetin, François Desbouvries
In this paper, we focus on the statistical filtering problem in dynamical models with jumps. When a particular application relies on physical properties which are modeled by linear…