Data-driven Model Reduction

Data-Driven Model Reduction is a model reduction technique that belongs to the class of reduced-order modeling methods, distinguished by its reliance on empirical data rather than explicit physical or mathematical equations to construct low-dimensional approximations of high-dimensional systems.

263

Publications

12.8K

Citations

638

Authors

294

Institutions

Publications per year

2017–2026

198

Variants

Data-driven Model Order Reduction

Authors

638

  1. KW
    Karen Willcox

    Massachusetts Institute of Technology, United States

    13 publications · 1.8K citations

    13

    h-index

  2. GR
    Gianluigi Rozza

    Scuola Internazionale Superiore di Studi Avanzati, Italy

    8 publications · 502 citations

    9

    h-index

  3. GH
    George Haller

    ETH Zurich, Switzerland

    8 publications · 377 citations

    8

    h-index

  4. BP
    Benjamin Peherstorfer

    Courant Institute of Mathematical Sciences, United States

    8 publications · 953 citations

    8

    h-index

  5. BK
    Boris Krämer

    University of California San Diego, United States

    5 publications · 231 citations

    6

    h-index

1–5 of 638

Venues

  1. 17

    h-index

  2. Journal of Computational Physics

    16 publications · 1.2K citations

    14

    h-index

  3. arXiv (Cornell University)

    Repository · 9 publications · 392 citations

    9

    h-index

  4. SIAM Journal on Scientific Computing

    8 publications · 855 citations

    9

    h-index

  5. Nonlinear Dynamics

    8 publications · 205 citations

    8

    h-index

1–5