Publication
Probabilistic and Bayesian methods for uncertainty quantification of deterministic and stochastic differential equations
Publications associées (463)
From low-rank retractions to dynamical low-rank approximation and back
Daniel Kressner, Axel Elie Joseph Séguin, Gianluca Ceruti
In algorithms for solving optimization problems constrained to a smooth manifold, retractions are a well-established tool to ensure that the iterates stay on the manifold. More recently, it has been demonstrated that retractions are a useful concept for ot ...
Springer2024Adaptive Finite Elements with Large Aspect Ratio. Application to Aluminium Electrolysis
The goal of this work is to use anisotropic adaptive finite elements for the numerical simulation of aluminium electrolysis. The anisotropic adaptive criteria are based on a posteriori error estimates derived for simplified problems. First, we consider an ...
EPFL2024Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks
Alfio Quarteroni, Francesco Regazzoni, Stefano Pagani
Predicting the evolution of systems with spatio-temporal dynamics in response to external stimuli is essential for scientific progress. Traditional equations-based approaches leverage first principles through the numerical approximation of differential equ ...
Nature Portfolio2024Anisotropic Adaptive Finite Elements for a p-Laplacian Problem
Marco Picasso, Paride Passelli
The p-Laplacian problem -del & sdot; ((mu + |del u|(p-2))del u) = f is considered, where mu is a given positive number. An anisotropic a posteriori residual-based error estimator is presented. The error estimator is shown to be equivalent, up to higher ord ...
Walter De Gruyter Gmbh2024SPACE-TIME REDUCED BASIS METHODS FOR PARAMETRIZED UNSTEADY STOKES EQUATIONS
Simone Deparis, Riccardo Tenderini, Nicholas Mueller
In this work, we analyze space-time reduced basis methods for the efficient numerical simulation of haemodynamics in arteries. The classical formulation of the reduced basis (RB) method features dimensionality reduction in space, while finite difference sc ...
Philadelphia2024Shape Holomorphy of Boundary Integral Operators on Multiple Open Arcs
Fernando José Henriquez Barraza
We establish shape holomorphy results for general weakly- and hyper-singular boundary integral operators arising from second-order partial differential equations in unbounded two-dimensional domains with multiple finite-length open arcs. After recasting th ...
New York2024Analytical Model of Single-Sided Linear Induction Motors for High-Speed Applications
André Hodder, Lucien André Félicien Pierrejean, Simone Rametti
This article describes a field-based analytical model of single-sided linear induction motors (SLIMs) that explicitly considers the following effects altogether: finite motor length, magnetomotive force mmf space harmonics, slot effect, edge effect, and ta ...
2024Reliable data-driven decision-making through optimal transport
Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks the ...
EPFL2024A Combination Technique for Optimal Control Problems Constrained by Random PDEs
We present a combination technique based on mixed differences of both spatial approximations and quadrature formulae for the stochastic variables to solve efficiently a class of optimal control problems (OCPs) constrained by random partial differential equ ...
2024Low-Rank Tensor Methods for High-Dimensional Problems
In this thesis, we propose and analyze novel numerical algorithms for solving three different high-dimensional problems involving tensors. The commonality of these problems is that the tensors can potentially be well approximated in low-rank formats. Ident ...
EPFL2023