Zobrazeno 1 - 10
of 215
pro vyhledávání: '"A. Dutfoy"'
We consider a model where a signal (discrete or continuous) is observed with an additive Gaussian noise process. The signal is issued from a linear combination of a finite but increasing number of translated features. The features are continuously pa
Externí odkaz:
http://arxiv.org/abs/2212.01169
In this paper we observe a set, possibly a continuum, of signals corrupted by noise. Each signal is a finite mixture of an unknown number of features belonging to a continuous dictionary. The continuous dictionary is parametrized by a real non-linear
Externí odkaz:
http://arxiv.org/abs/2210.16311
Using Bayesian methods for extreme value analysis offers an alternative to frequentist ones, with several advantages such as easily dealing with parametric uncertainty or studying irregular models. However, computations can be challenging and the eff
Externí odkaz:
http://arxiv.org/abs/2210.05224
Adaptive importance sampling based on fault tree analysis for piecewise deterministic Markov process
Piecewise deterministic Markov processes (PDMPs) can be used to model complex dynamical industrial systems. The counterpart of this modeling capability is their simulation cost, which makes reliability assessment untractable with standard Monte Carlo
Externí odkaz:
http://arxiv.org/abs/2210.16185
We consider a general non-linear model where the signal is a finite mixture of an unknown, possibly increasing, number of features issued from a continuous dictionary parameterized by a real nonlinear parameter. The signal is observed with Gaussian (
Externí odkaz:
http://arxiv.org/abs/2207.00171
Diagnosing convergence of Markov chain Monte Carlo is crucial and remains an essentially unsolved problem. Among the most popular methods, the potential scale reduction factor, commonly named $\hat{R}$, is an indicator that monitors the convergence o
Externí odkaz:
http://arxiv.org/abs/2205.06694
Publikováno v:
In Computational Statistics and Data Analysis November 2023 187
Variance reduction methods are often needed for the reliability assessment of complex industrial systems, we focus on one variance reduction method in a given context, that is the interacting particle system method (IPS) used on piecewise determinist
Externí odkaz:
http://arxiv.org/abs/1905.09044
The assessment of the probability of a rare event with a naive Monte-Carlo method is computationally intensive, so faster estimation or variance reduction methods are needed. We focus on one of these methods which is the interacting particle system (
Externí odkaz:
http://arxiv.org/abs/1811.10450
The reliability of a complex industrial system can rarely be assessed analytically. As system failure is often a rare event, crude Monte-Carlo methods are prohibitively expensive from a computational point of view. In order to reduce computation time
Externí odkaz:
http://arxiv.org/abs/1707.08136