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Frédéric Cérou

Researcher at French Institute for Research in Computer Science and Automation

Publications -  51
Citations -  2135

Frédéric Cérou is an academic researcher from French Institute for Research in Computer Science and Automation. The author has contributed to research in topics: Monte Carlo method & Markov process. The author has an hindex of 21, co-authored 51 publications receiving 1998 citations. Previous affiliations of Frédéric Cérou include University of Rennes & Alcatel-Lucent.

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Journal ArticleDOI

Adaptive Multilevel Splitting for Rare Event Analysis

TL;DR: This article proposes an adaptive algorithm to cope with the estimation of rare event probability that is asymptotically consistent, costs just a little bit more than classical multilevel splitting, and has the same efficiency in terms of asymPTotic variance.
Journal ArticleDOI

Sequential Monte Carlo for rare event estimation

TL;DR: A novel strategy for simulating rare events and an associated Monte Carlo estimation of tail probabilities using a system of interacting particles and exploits a Feynman-Kac representation of that system to analyze their fluctuations.
Journal ArticleDOI

Two mode transmission at 2x100Gb/s, over 40km-long prototype few-mode fiber, using LCOS-based programmable mode multiplexer and demultiplexer

TL;DR: A novel optical transmission system based on a programmable liquid crystal on silicon panel, a prototype few-mode fiber, and a 4×4 multiple input multiple output algorithm processing the information of two polarization diversity coherent receivers to experimentally demonstrate the possibility of mode division multiplexing.
Proceedings ArticleDOI

Transmission at 2×100Gb/s, over two modes of 40km-long prototype few-mode fiber, using LCOS-based mode multiplexer and demultiplexer

TL;DR: In this paper, two 100Gb/s PDMQPSK data streams over two different modes of a 40km-long prototype few-mode fiber were transmitted with an LCOS-based mode multiplexer/demultiplexer and 4×4 MIMO algorithm in a coherent receiver.
Journal ArticleDOI

A nonasymptotic theorem for unnormalized Feynman-Kac particle models

TL;DR: In this article, a nonasymptotic theorem for interacting particle approximations of unnormalized Feynman-Kac models is presented, where the L(2)-relative error of these weighted particle measures grows linearly with respect to the time horizon.