Arnaud Guyader
YOU?
Author Swipe
On deviation probabilities in non-parametric regression with heavy-tailed noise Open
This paper is devoted to the problem of determining the concentration bounds that are achievable in non-parametric regression. We consider the setting where features are supported on a bounded subset of $\mathbb{R}^d$, the regression funct…
View article: Recursive Estimation of a Failure Probability for a Lipschitz Function
Recursive Estimation of a Failure Probability for a Lipschitz Function Open
Let denote a Lipschitz function that can be evaluated at each point, but at the price of a heavy computational time. Let stand for a random variable with values in such that one is able to simulate, at least approximately, according to the…
View article: Recursive Estimation of a Failure Probability for a Lipschitz Function
Recursive Estimation of a Failure Probability for a Lipschitz Function Open
Let g : $Ω$ = [0, 1] d $\rightarrow$ R denote a Lipschitz function that can be evaluated at each point, but at the price of a heavy computational time. Let X stand for a random variable with values in $Ω$ such that one is able to simulate,…
Variance estimation in adaptive sequential Monte Carlo Open
International audience
On synchronized Fleming–Viot particle systems Open
39 pages, 3 figures
On the Hill relation and the mean reaction time for metastable processes Open
We illustrate how the Hill relation and the notion of quasi-stationary distribution can be used to analyse the biasing error introduced by many numerical procedures that have been proposed in the literature, in particular in molecular dyna…
On Synchronized Fleming-Viot Particle Systems Open
This article presents a variant of Fleming-Viot particle systems, which are a\nstandard way to approximate the law of a Markov process with killing as well as\nrelated quantities. Classical Fleming-Viot particle systems proceed by\nsimulat…
On Synchronized Fleming-Viot Particle Systems Open
This article presents a variant of Fleming-Viot particle systems, which are a standard way to approximate the law of a Markov process with killing as well as related quantities. Classical Fleming-Viot particle systems proceed by simulating…
Variance Estimation in Adaptive Sequential Monte Carlo Open
Sequential Monte Carlo (SMC) methods represent a classical set of techniques to simulate a sequence of probability measures through a simple selection/mutation mechanism. However, the associated selection functions and mutation kernels usu…
Adaptive multilevel splitting: Historical perspective and recent results Open
This article first presents a short historical perpective of the importance splitting approach to simulate and estimate rare events, with a detailed description of several variants. We then give an account of recent theoretical results on …
View article: On the Asymptotic Normality of Adaptive Multilevel Splitting
On the Asymptotic Normality of Adaptive Multilevel Splitting Open
Adaptive Multilevel Splitting (AMS for short) is a generic Monte Carlo method for Markov processes that simulates rare events and estimates associated probabilities. Despite its practical efficiency, there are almost no theoretical results…
Rare event simulation for molecular dynamics Open
This talk is devoted to the presentation of algorithms for simulating rare events in a molecular dynamics context, e.g., the simulation of reactive paths. We will consider $\mathbb{R}^d$ as the space of configurations for a given system, w…
View article: A Central Limit Theorem for Fleming-Viot Particle Systems with Hard Killing
A Central Limit Theorem for Fleming-Viot Particle Systems with Hard Killing Open
Fleming-Viot type particle systems represent a classical way to approximate the distribution of a Markov process with killing, given that it is still alive at a final deterministic time. In this context, each particle evolves independently…
View article: A Central Limit Theorem for Fleming-Viot Particle Systems with Hard\n Killing
A Central Limit Theorem for Fleming-Viot Particle Systems with Hard\n Killing Open
Fleming-Viot type particle systems represent a classical way to approximate\nthe distribution of a Markov process with killing, given that it is still alive\nat a final deterministic time. In this context, each particle evolves\nindependen…
Fluctuation analysis of adaptive multilevel splitting Open
Multilevel Splitting is a Sequential Monte Carlo method to simulate realisations of a rare event as well as to estimate its probability. This article is concerned with the convergence and the fluctuation analysis of Adaptive Multilevel Spl…
View article: A Central Limit Theorem for Fleming-Viot Particle Systems with Soft Killing
A Central Limit Theorem for Fleming-Viot Particle Systems with Soft Killing Open
The distribution of a Markov process with killing, conditioned to be still alive at a given time, can be approximated by a Fleming-Viot type particle system. In such a system, each particle is simulated independently according to the law o…