Large deformation shape uncertainty quantification in acoustic scattering. - Ralf Hiptmair; Laura Scarabosio; Claudia Schillings; Christoph Schwab (Adv. Comput. Math., 2018)

Goal-oriented adaptive modeling of random heterogeneous media and model-based multilevel Monte Carlo methods. - Laura Scarabosio; Barbara I. Wohlmuth; J. Tinsley Oden; Danial Faghihi (Comput. Math. Appl., 2019)

Analysis of Boundary Effects on PDE-Based Sampling of Whittle-Matérn Random Fields. - Ustim Khristenko; Laura Scarabosio; Piotr Swierczynski; Elisabeth Ullmann; Barbara I. Wohlmuth (SIAM/ASA J. Uncertain. Quantification, 2019)

On a subdiffusive tumour growth model with fractional time derivative. - Marvin Fritz; Christina Kuttler; Mabel L. Rajendran; Laura Scarabosio; Barbara I. Wohlmuth (CoRR, 2020)

Deep neural network surrogates for non-smooth quantities of interest in shape uncertainty quantification. - Laura Scarabosio (CoRR, 2021)

Environmental stress level to model tumor cell growth and survival. - Sabrina Schönfeld; Alican Ozkan; Laura Scarabosio; Marissa Nichole Rylander; Christina Kuttler (CoRR, 2022)

Deep Neural Network Surrogates for Nonsmooth Quantities of Interest in Shape Uncertainty Quantification. - Laura Scarabosio (SIAM/ASA J. Uncertain. Quantification, 2022)

Exploiting locality in sparse polynomial approximation of parametric elliptic PDEs and application to parameterized domains. - Wouter van Harten; Laura Scarabosio (CoRR, 2023)

Distributed preconditioning for the parametric Helmholtz equation. - Wouter van Harten; Laura Scarabosio (CoRR, 2025)