activity
20062026
most citedMultilevel Sequential Monte Carlo Samplers

113 citations · 1k across the 84 of their papers we have counts for

collaborators

97 papers

math.NA2026

On the sample complexity of the active subspace method

Fabio Nobile, Matteo Raviola, Raúl Tempone

Active subspaces identify low-dimensional linear structure in high-dimensional parameter-to-output maps by estimating the dominant eigenspace of a gradient covariance operator. In…

math.NA2025

A function approximation algorithm using multilevel active subspaces

Fabio Nobile, Matteo Raviola, Raul Tempone

The Active Subspace (AS) method is a widely used technique for identifying the most influential directions in high-dimensional input spaces that affect the output of a computationa…

eess.SP2024

Stochastic differential equations for performance analysis of wireless communication systems

Eya Ben Amar, Nadhir Ben Rached, Raul Tempone +1

This paper addresses the difficulty of characterizing the time-varying nature of fading channels. The current time-invariant models often fall short of capturing and tracking these…

math.NA2023

Multi-index importance sampling for McKean--Vlasov stochastic differential equations

Nadhir Ben Rached, Abdul-Lateef Haji-Ali, Shyam Mohan Subbiah Pillai +1

This work addresses the estimation of rare-event quantities expressed as expectations of smooth observables of solutions to a broad class of McKean--Vlasov stochastic differential…

math.NA2023

Scalable method for Bayesian experimental design without integrating over posterior distribution

Vinh Hoang, Luis Espath, Sebastian Krumscheid +1

We address the computational efficiency in solving the A-optimal Bayesian design of experiments problems for which the observational map is based on partial differential equations…

math.NA2023★ 2 cited

Automated Importance Sampling via Optimal Control for Stochastic Reaction Networks: A Markovian Projection-based Approach

Chiheb Ben Hammouda, Nadhir Ben Rached, Raúl Tempone +1

We propose a novel alternative approach to our previous work (Ben Hammouda et al., 2023) to improve the efficiency of Monte Carlo (MC) estimators for rare event probabilities for s…