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Benjamin Peherstorfer
Researcher at New York University
Publications - 84
Citations - 3579
Benjamin Peherstorfer is an academic researcher from New York University. The author has contributed to research in topics: Computer science & Sparse grid. The author has an hindex of 23, co-authored 71 publications receiving 2317 citations. Previous affiliations of Benjamin Peherstorfer include Massachusetts Institute of Technology & Courant Institute of Mathematical Sciences.
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Survey of Multifidelity Methods in Uncertainty Propagation, Inference, and Optimization
TL;DR: In many situations across computational science and engineering, multiple computational models are available that describe a system of interest as discussed by the authors, and these different models have varying evaluation costs, i.e.
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Data-driven operator inference for nonintrusive projection-based model reduction
TL;DR: In this article, a nonintrusive projection-based model reduction approach for full models based on time-dependent partial differential equations is presented, which is applicable to full models that are linear in the state or have a low-order polynomial nonlinear term.
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Projection-based model reduction: Formulations for physics-based machine learning
TL;DR: The case studies demonstrate the importance of embedding physical constraints within learned models, and highlight the important point that the amount of model training data available in an engineering setting is often much less than it is in other machine learning applications, making it essential to incorporate knowledge from physical models.
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Localized Discrete Empirical Interpolation Method
TL;DR: This paper presents a new approach to construct more efficient reduced-order models for nonlinear partial differential equations with proper orthogonal decomposition and the discrete empirical interpolation method (DEIM).
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Online adaptive model reduction for nonlinear systems via low-rank updates ∗
TL;DR: This research presents a novel, scalable, scalable and scalable approaches to solve the challenge of integrating NoSQL data stores to manage and manage distributed systems.