7 citations · 19 across the 21 of their papers we have counts for
11 papers · 1 filter
An analysis of the noise schedule for score-based generative models
Stanislas Strasman, Antonio Ocello, Claire Boyer +2
Score-based generative models (SGMs) aim at estimating a target data distribution by learning score functions using only noise-perturbed samples from the target.Recent literature h…
Learning the distribution of latent variables in paired comparison models with round-robin scheduling
Roland Diel, Sylvain Le Corff, Matthieu Lerasle
Paired comparison data considered in this paper originate from the comparison of a large number N of individuals in couples. The dataset is a collection of results of contests betw…
Stochastic differential equation based on a multimodal potential to model movement data in ecology
Pierre Gloaguen, Marie-Pierre Etienne, Sylvain Le Corff
This paper proposes a new model for individuals movement in ecology. The movement process is defined as a solution to a stochastic differential equation whose drift is the gradient…
Consistent estimation of the filtering and marginal smoothing distributions in nonparametric hidden Markov models
Yohann De Castro, Elisabeth Gassiat, Sylvain Le Corff
In this paper, we consider the filtering and smoothing recursions in nonparametric finite state space hidden Markov models (HMMs) when the parameters of the model are unknown and r…
Statistical Inference for Oscillation Processes
Rainer Dahlhaus, Thierry Dumont, Sylvain Le Corff +1
A new model for time series with a specific oscillation pattern is proposed. The model consists of a hidden phase process controlling the speed of polling and a nonparametric curve…
A shrinkage-thresholding Metropolis adjusted Langevin algorithm for Bayesian variable selection
Amandine Schreck, Gersende Fort, Sylvain Le Corff +1
This paper introduces a new Markov Chain Monte Carlo method for Bayesian variable selection in high dimensional settings. The algorithm is a Hastings-Metropolis sampler with a prop…
Nonparametric regression on hidden phi-mixing variables: identifiability and consistency of a pseudo-likelihood based estimation procedure
Thierry Dumont, Sylvain Le Corff
This paper outlines a new nonparametric estimation procedure for unobserved phi-mixing processes. It is assumed that the only information on the stationary hidden states (Xk) is gi…
Convergence of a Particle-based Approximation of the Block Online Expectation Maximization Algorithm
Sylvain Le Corff, Gersende Fort
Online variants of the Expectation Maximization (EM) algorithm have recently been proposed to perform parameter inference with large data sets or data streams, in independent laten…
Supplement paper to "Online Expectation Maximization based algorithms for inference in hidden Markov models"
Sylvain Le Corff, Gersende Fort
This is a supplementary material to the paper "Online Expectation Maximization based algorithms for inference in hidden Markov models". It contains further technical derivations an…
Online Expectation Maximization based algorithms for inference in hidden Markov models
Sylvain Le Corff, Gersende Fort
The Expectation Maximization (EM) algorithm is a versatile tool for model parameter estimation in latent data models. When processing large data sets or data stream however, EM bec…
Non-asymptotic deviation inequalities for smoothed additive functionals in non-linear state-space models
Cyrille Dubarry, Sylvain Le Corff
The approximation of fixed-interval smoothing distributions is a key issue in inference for general state-space hidden Markov models (HMM). This contribution establishes non-asympt…