Physics-informed regularization and structure preservation for learning stable reduced models from data with operator inference

6 July 2021

Papers citing "Physics-informed regularization and structure preservation for learning stable reduced models from data with operator inference"

7 / 7 papers shown

Title
System stabilization with policy optimization on unstable latent manifolds Steffen W. R. Werner Benjamin Peherstorfer 33 1 0 08 Jul 2024
Learning reduced-order Quadratic-Linear models in Process Engineering using Operator Inference I. V. Gosea Luisa Peterson P. Goyal J. Bremer Kai Sundmacher Peter Benner AI4CE 14 1 0 27 Feb 2024
Data-Driven Discovery of PDEs via the Adjoint Method Mohsen Sadr Tony Tohme Kamal Youcef-Toumi PINN 27 1 0 30 Jan 2024
Nonlinear embeddings for conserving Hamiltonians and other quantities with Neural Galerkin schemes Paul Schwerdtner Philipp Schulze Jules Berman Benjamin Peherstorfer 21 6 0 11 Oct 2023
Guaranteed Stable Quadratic Models and their applications in SINDy and Operator Inference P. Goyal I. P. Duff P. Benner 12 14 0 26 Aug 2023
Inference of Continuous Linear Systems from Data with Guaranteed Stability P. Goyal I. P. Duff P. Benner 19 4 0 24 Jan 2023
Operator inference with roll outs for learning reduced models from scarce and low-quality data W. I. Uy D. Hartmann Benjamin Peherstorfer AI4CE 25 15 0 02 Dec 2022