Artigos com autorizações de acesso público - Benjamin PeherstorferSaiba mais
2 artigos não disponíveis publicamente
Multifidelity Monte Carlo estimation with adaptive low-fidelity models
B Peherstorfer
SIAM/ASA Journal on Uncertainty Quantification 7 (2), 579-603, 2019
Autorizações: US Department of Defense
Parametric model order reduction by sparse-grid-based interpolation on matrix manifolds for multidimensional parameter spaces
M Geuss, D Butnaru, B Peherstorfer, HJ Bungartz, B Lohmann
2014 European Control Conference (ECC), 2727-2732, 2014
Autorizações: German Research Foundation
47 artigos disponíveis publicamente
Survey of multifidelity methods in uncertainty propagation, inference, and optimization
B Peherstorfer, K Willcox, M Gunzburger
SIAM Review 60 (3), 550-591, 2018
Autorizações: US Department of Energy, US Department of Defense
Data-driven operator inference for nonintrusive projection-based model reduction
B Peherstorfer, K Willcox
Computer Methods in Applied Mechanics and Engineering 306, 196-215, 2016
Autorizações: US Department of Energy
Projection-based model reduction: Formulations for physics-based machine learning
R Swischuk, L Mainini, B Peherstorfer, K Willcox
Computers & Fluids 179, 704-717, 2019
Autorizações: US Department of Defense
Optimal model management for multifidelity Monte Carlo estimation
B Peherstorfer, K Willcox, M Gunzburger
SIAM Journal on Scientific Computing 38 (5), A3163-A3194, 2016
Autorizações: US Department of Energy
Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems
E Qian, B Kramer, B Peherstorfer, K Willcox
Physica D: Nonlinear Phenomena 406, 132401, 2020
Autorizações: US National Science Foundation, US Department of Energy, US Department of …
Model Reduction for Transport-Dominated Problems via Online Adaptive Bases and Adaptive Sampling
B Peherstorfer
SIAM Journal on Scientific Computing 42 (5), A2803-A2836, 2020
Autorizações: US Department of Defense
Multifidelity importance sampling
B Peherstorfer, T Cui, Y Marzouk, K Willcox
Computer Methods in Applied Mechanics and Engineering, 2015
Autorizações: US Department of Energy
Operator inference for non-intrusive model reduction of systems with non-polynomial nonlinear terms
P Benner, P Goyal, B Kramer, B Peherstorfer, K Willcox
Computer Methods in Applied Mechanics and Engineering 372, 113433, 2020
Autorizações: US National Science Foundation, US Department of Energy, US Department of …
Stability of discrete empirical interpolation and gappy proper orthogonal decomposition with randomized and deterministic sampling points
B Peherstorfer, Z Drmač, S Gugercin
SIAM Journal on Scientific Computing 42 (5), A2837-A2864, 2020
Autorizações: US National Science Foundation, US Department of Defense
Multifidelity Monte Carlo estimation of variance and sensitivity indices
E Qian, B Peherstorfer, D O'Malley, VV Vesselinov, K Willcox
SIAM/ASA Journal on Uncertainty Quantification 6 (2), 683-706, 2018
Autorizações: US National Science Foundation, US Department of Energy, US Department of …
Data-Driven Reduced Model Construction with Time-Domain Loewner Models
B Peherstorfer, S Gugercin, K Willcox
SIAM Journal on Scientific Computing 39 (5), A2152-A2178, 2017
Autorizações: US National Science Foundation
Geometric subspace updates with applications to online adaptive nonlinear model reduction
R Zimmermann, B Peherstorfer, K Willcox
SIAM Journal on Matrix Analysis and Applications 39 (1), 234-261, 2018
Autorizações: US Department of Energy, US Department of Defense, German Research Foundation
Manifold Approximations via Transported Subspaces: Model Reduction for Transport-Dominated Problems
D Rim, B Peherstorfer, KT Mandli
SIAM Journal on Scientific Computing 45 (1), A170-A199, 2023
Autorizações: US National Science Foundation, US Department of Defense
Breaking the Kolmogorov Barrier with Nonlinear Model Reduction
B Peherstorfer
Notices of the American Mathematical Society 69 (5), 725-733, 2022
Autorizações: US National Science Foundation, US Department of Defense
Neural Galerkin schemes with active learning for high-dimensional evolution equations
J Bruna, B Peherstorfer, E Vanden-Eijnden
Journal of Computational Physics 496, 112588, 2024
Autorizações: US National Science Foundation, US Department of Defense
Sampling low-dimensional Markovian dynamics for preasymptotically recovering reduced models from data with operator inference
B Peherstorfer
SIAM Journal on Scientific Computing 42 (5), A3489-A3515, 2020
Autorizações: US National Science Foundation, US Department of Energy
Combining multiple surrogate models to accelerate failure probability estimation with expensive high-fidelity models
B Peherstorfer, B Kramer, K Willcox
Journal of Computational Physics, 2017
Autorizações: US Department of Defense
Multifidelity preconditioning of the cross-entropy method for rare event simulation and failure probability estimation
B Peherstorfer, B Kramer, K Willcox
SIAM/ASA Journal on Uncertainty Quantification 6 (2), 737-761, 2018
Autorizações: US Department of Defense
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