3 citations · 3 across the 10 of their papers we have counts for
10 papers
Multilevel Stochastic Gradient Descent for Risk-Averse PDE-Constrained Optimization
Niklas Baumgarten, Philipp A. Guth, David Schneiderhan +1
We present recent advances in applying and analyzing multilevel stochastic gradient descent algorithms to risk-averse, three-dimensional PDE-constrained optimization problems. The…
Optimized multilevel Monte Carlo methods in Banach spaces
Kristin Kirchner, Fabio Nobile, Christoph Schwab +1
We present a theoretical and numerical analysis of Monte Carlo methods for the estimation of statistical moments of random variables taking values in a Banach sp…
Low-rank solutions to a class of parametrized systems using Riemannian optimization
Marco Sutti, Tommaso Vanzan
We propose a computational framework for computing low-rank approximations to the ensemble of solutions of a parametrized system of the form for multiple pa…
LAGO: A Local-Global Optimization Framework Combining Trust Region Methods and Bayesian Optimization
Eliott Van Dieren, Tommaso Vanzan, Fabio Nobile
We introduce LAGO, a LocAl-Global Optimization framework coupling Bayesian Optimization (BO) and gradient-based trust region local refinement through an adaptive competition mechan…
An adaptive importance sampling algorithm for risk-averse optimization
Sandra Pieraccini, Tommaso Vanzan
Adaptive sampling algorithms are modern and efficient methods that dynamically adjust the sample size throughout the optimization process. However, they may encounter difficulties…
Variable reduction as a nonlinear preconditioning approach for optimization problems
Gabriele Ciaremalla, Tommaso Vanzan
When considering an unconstrained minimization problem, a standard approach is to solve the optimality system with a Newton method possibly preconditioned by, e.g., nonlinear elimi…
Nonlinear Schwarz methods to compute geodesics on manifolds
Marco Sutti, Tommaso Vanzan
We consider the leapfrog algorithm by Noakes for computing geodesics on Riemannian manifolds. The main idea behind this algorithm is to subdivide the original endpoint geodesic pro…
Optimized Schwarz methods for the time-dependent Stokes-Darcy coupling
Marco Discacciati, Tommaso Vanzan
This paper derives optimal coefficients for optimized Schwarz iterations for the time-dependent Stokes-Darcy problem using an innovative strategy to solve a nonstandard min-max pro…
Weak scalability of domain decomposition methods for discrete fracture networks
Stefano Berrone, Tommaso Vanzan
Discrete Fracture Networks (DFNs) are complex three-dimensional structures characterized by the intersections of planar polygonal fractures, and are used to model flows in fracture…
Quantum thermostatted disordered systems and sensitivity under compression
Tommaso Vanzan, Lamberto Rondoni
A one-dimensional quantum system with off diagonal disorder, consisting of a sample of conducting regions randomly interspersed within potential barriers is considered. Results mai…