research
∙
01/31/2023
Application of dimension truncation error analysis to high-dimensional function approximation
Parametric mathematical models such as partial differential equations wi...
share
research
∙
09/13/2022
Generalized dimension truncation error analysis for high-dimensional numerical integration: lognormal setting and beyond
Partial differential equations (PDEs) with uncertain or random inputs ha...
research
∙
08/04/2022
Parabolic PDE-constrained optimal control under uncertainty with entropic risk measure using quasi-Monte Carlo integration
We study the application of a tailored quasi-Monte Carlo (QMC) method to...
research
∙
12/21/2021
A General Framework for Machine Learning based Optimization Under Uncertainty
We propose a general framework for machine learning based optimization u...
research
∙
09/29/2021
Multilevel Quasi-Monte Carlo for Optimization under Uncertainty
This paper considers the problem of optimizing the average tracking erro...
research
∙
05/05/2020
Ensemble Kalman filter for neural network based one-shot inversion
We study the use of novel techniques arising in machine learning for inv...
research
∙
10/22/2019
