Personne
Fabio Nobile
Publications associées (185)
Parametric Reduced Order Model of a Gas Bearings Supported Rotor
Fabio Nobile, Jürg Alexander Schiffmann, Dimitri Maurice Goutaudier
Gas bearings use pressurized gas as a lubricant to support and guide rotating machinery. These bearings have a number of advantages over traditional lubricated bearings, including higher efficiency in a variety of applications and reduced maintenance requi ...
2024Error estimates for SUPG-stabilised Dynamical Low Rank Approximations
Fabio Nobile, Thomas Simon Spencer Trigo Trindade
We perform an error analysis of a fully discretised Streamline Upwind Petrov Galerkin Dynamical Low Rank (SUPG-DLR) method for random time-dependent advection-dominated problems. The time integration scheme has a splitting-like nature, allowing for potenti ...
2024A 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 ...
2024Analysis of a Class of Multilevel Markov Chain Monte Carlo Algorithms Based on Independent Metropolis–Hastings
Fabio Nobile, Juan Pablo Madrigal Cianci
In this work, we present, analyze, and implement a class of multilevel Markov chain Monte Carlo(ML-MCMC) algorithms based on independent Metropolis--Hastings proposals for Bayesian inverse problems. In this context, the likelihood function involves solving ...
2023A multigrid method for PDE-constrained optimization with uncertain inputs
We present a multigrid algorithm to solve efficiently the large saddle-point systems of equations that typically arise in PDE-constrained optimization under uncertainty. The algorithm is based on a collective smoother that at each iteration sweeps over the ...
2023Density Estimation In Rkhs With Application To Korobov Spaces In High Dimensions
Fabio Nobile, Yoshihito Kazashi
A kernel method for estimating a probability density function from an independent and identically distributed sample drawn from such density is presented. Our estimator is a linear combination of kernel functions, the coefficients of which are determined b ...
SIAM PUBLICATIONS2023Dynamically Orthogonal Approximation for Stochastic Differential Equations
Fabio Nobile, Yoshihito Kazashi, Fabio Zoccolan
In this paper, we set the mathematical foundations of the Dynamical Low Rank Approximation (DLRA) method for high-dimensional stochastic differential equations. DLRA aims at approximating the solution as a linear combination of a small number of basis vect ...
2023Parametric Reduced Order Model of a Gas Bearings Supported Rotor
Fabio Nobile, Jürg Alexander Schiffmann, Dimitri Maurice Goutaudier
Gas bearings use pressurized gas as a lubricant to support and guide rotating machinery. These bearings have a number of advantages over traditional lubricated bearings, including higher efficiency in a variety of applications and reduced maintenance requi ...
2023Gradient-based optimisation of the conditional-value-at-risk using the multi-level Monte Carlo method
Fabio Nobile, Sundar Subramaniam Ganesh
In this work, we tackle the problem of minimising the Conditional-Value-at-Risk (CVaR) of output quantities of complex differential models with random input data, using gradient-based approaches in combination with the Multi-Level Monte Carlo (MLMC) method ...
2022Quantifying uncertain system outputs via the multi-level Monte Carlo method --- distribution and robustness measures
Fabio Nobile, Sebastian Krumscheid, Sundar Subramaniam Ganesh
In this work, we consider the problem of estimating the probability distribution, the quantile or the conditional expectation above the quantile, the so called conditional-value-at-risk, of output quantities of complex random differential models by the MLM ...
2022