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Benjamin Peherstorfer
Benjamin Peherstorfer
Courant Institute of Mathematical Sciences, New York University
Verified email at cims.nyu.edu - Homepage
Title
Cited by
Cited by
Year
Survey of multifidelity methods in uncertainty propagation, inference, and optimization
B Peherstorfer, K Willcox, M Gunzburger
SIAM Review 60 (3), 550-591, 2018
9992018
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
3952016
Projection-based model reduction: Formulations for physics-based machine learning
R Swischuk, L Mainini, B Peherstorfer, K Willcox
Computers & Fluids 179, 704-717, 2019
3482019
Optimal model management for multifidelity Monte Carlo estimation
B Peherstorfer, K Willcox, M Gunzburger
SIAM Journal on Scientific Computing 38 (5), A3163-A3194, 2016
2782016
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
2722020
Localized discrete empirical interpolation method
B Peherstorfer, D Butnaru, K Willcox, HJ Bungartz
SIAM Journal on Scientific Computing 36 (1), 2014
2712014
Dynamic data-driven reduced-order models
B Peherstorfer, K Willcox
Computer Methods in Applied Mechanics and Engineering 291, 21-41, 2015
2082015
Online Adaptive Model Reduction for Nonlinear Systems via Low-Rank Updates
B Peherstorfer, K Willcox
SIAM Journal on Scientific Computing 37 (4), A2123-A2150, 2015
2002015
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
1422020
Multifidelity importance sampling
B Peherstorfer, T Cui, Y Marzouk, K Willcox
Computer Methods in Applied Mechanics and Engineering, 2015
1412015
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
1092020
Spatially adaptive sparse grids for high-dimensional data-driven problems
D Pflüger, B Peherstorfer, HJ Bungartz
Journal of Complexity 26 (5), 508-522, 2010
1022010
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
932020
Analysis of Car Crash Simulation Data with Nonlinear Machine Learning Methods
B Bohn, J Garcke, R Iza-Teran, A Paprotny, B Peherstorfer, ...
Procedia Computer Science 18, 621-630, 2013
912013
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
872017
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
832018
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
732018
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
59*2023
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
532018
Density Estimation with Adaptive Sparse Grids for Large Data Sets
B Peherstorfer, D Pflüge, HJ Bungartz
SIAM Data Mining 2014, 2014
512014
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