3 citations · 5 across the 2 of their papers we have counts for
3 papers
math.NA2024
Sparsifying dimensionality reduction of PDE solution data with Bregman learning
Tjeerd Jan Heeringa, Christoph Brune, Mengwu Guo
Classical model reduction techniques project the governing equations onto a linear subspace of the original state space. More recent data-driven techniques use neural networks to e…
cs.LG2023★ 3 cited
Multi-fidelity reduced-order surrogate modeling
Paolo Conti, Mengwu Guo, Andrea Manzoni +3
High-fidelity numerical simulations of partial differential equations (PDEs) given a restricted computational budget can significantly limit the number of parameter configurations…
math.NA2023★ 2 cited
Uncertainty quantification for nonlinear solid mechanics using reduced order models with Gaussian process regression
Ludovica Cicci, Stefania Fresca, Mengwu Guo +2
Uncertainty quantification (UQ) tasks, such as sensitivity analysis and parameter estimation, entail a huge computational complexity when dealing with input-output maps involving t…