activity
20122020
most citedParticle rejuvenation of Rao-Blackwellized Sequential Monte Carlo smoothers for Conditionally Linear and Gaussian models

4 citations · 8 across the 3 of their papers we have counts for

collaborators

8 papers

cs.LG20216 cited

Joint self-supervised blind denoising and noise estimation

Jean Ollion, Charles Ollion, Elisabeth Gassiat +2

We propose a novel self-supervised image blind denoising approach in which two neural networks jointly predict the clean signal and infer the noise distribution. Assuming that the…

cs.LG2020

The Monte Carlo Transformer: a stochastic self-attention model for sequence prediction

Alice Martin, Charles Ollion, Florian Strub +2

This paper introduces the Sequential Monte Carlo Transformer, an original approach that naturally captures the observations distribution in a transformer architecture. The keys, qu…

eess.SP20204 cited

End-to-end deep metamodeling to calibrate and optimize energy loads

Max Cohen, Maurice Charbit, Sylvain Le Corff +2

In this paper, we propose a new end-to-end methodology to optimize the energy performance and the comfort, air quality and hygiene of large buildings. A metamodel based on a Transf…

stat.CO2019

A pseudo-marginal sequential Monte Carlo online smoothing algorithm

Pierre Gloaguen, Sylvain Le Corff, Jimmy Olsson

We consider online computation of expectations of additive state functionals under general path probability measures proportional to products of unnormalised transition densities.…

math.ST2019

Identifiability and consistent estimation of nonparametric translation hidden Markov models with general state space

Elisabeth Gassiat, Sylvain Le Corff, Luc Lehéricy

This paper considers hidden Markov models where the observations are given as the sum of a latent state which lies in a general state space and some independent noise with unknown…

math.ST2018

A Bayesian nonparametric approach for generalized Bradley-Terry models in random environment

Sylvain Le Corff, Matthieu Lerasle, Elodie Vernet

This paper deals with the estimation of the unknown distribution of hidden random variables from the observation of pairwise comparisons between these variables. This problem is in…