44 citations · 107 across the 24 of their papers we have counts for
4 papers · 2 filters
Context-aware surrogate modeling for balancing approximation and sampling costs in multi-fidelity importance sampling and Bayesian inverse problems
Terrence Alsup, Benjamin Peherstorfer
Multi-fidelity methods leverage low-cost surrogate models to speed up computations and make occasional recourse to expensive high-fidelity models to establish accuracy guarantees.…
Depth separation for reduced deep networks in nonlinear model reduction: Distilling shock waves in nonlinear hyperbolic problems
Donsub Rim, Luca Venturi, Joan Bruna +1
Classical reduced models are low-rank approximations using a fixed basis designed to achieve dimensionality reduction of large-scale systems. In this work, we introduce reduced dee…
Probabilistic error estimation for non-intrusive reduced models learned from data of systems governed by linear parabolic partial differential equations
Wayne Isaac Tan Uy, Benjamin Peherstorfer
This work derives a residual-based a posteriori error estimator for reduced models learned with non-intrusive model reduction from data of high-dimensional systems governed by line…
Operator inference for non-intrusive model reduction of systems with non-polynomial nonlinear terms
Peter Benner, Pawan Goyal, Boris Kramer +2
This work presents a non-intrusive model reduction method to learn low-dimensional models of dynamical systems with non-polynomial nonlinear terms that are spatially local and that…