Hamzi, Boumediene and Owhadi, Houman (2020) Learning dynamical systems from data: a simple cross-validation perspective. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20201109-155527819
![[img]](https://authors.library.caltech.edu/style/images/fileicons/application_pdf.png) |
PDF
- Submitted Version
See Usage Policy. 1MB |
Use this Persistent URL to link to this item: https://resolver.caltech.edu/CaltechAUTHORS:20201109-155527819
Abstract
Regressing the vector field of a dynamical system from a finite number of observed states is a natural way to learn surrogate models for such systems. We present variants of cross-validation (Kernel Flows [31] and its variants based on Maximum Mean Discrepancy and Lyapunov exponents) as simple approaches for learning the kernel used in these emulators.
| Item Type: | Report or Paper (Discussion Paper) | ||||||
|---|---|---|---|---|---|---|---|
| Related URLs: |
| ||||||
| ORCID: |
| ||||||
| Additional Information: | B. H. thanks the European Commission for funding through the Marie Curie fellowship STALDYS-792919 (Statistical Learning for Dynamical Systems). H. O. gratefully acknowledges support by the Air Force Office of Scientific Research under award number FA9550-18-1-0271 (Games for Computation and Learning). We thank Deniz Eroğlu, Yoshito Hirata, Jeroen Lamb, Edmilson Roque, Gabriele Santin and Yuzuru Sato for useful comments. | ||||||
| Funders: |
| ||||||
| Record Number: | 10.13140/RG.2.2.24823.44964 | ||||||
| Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20201109-155527819 | ||||||
| Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||
| ID Code: | 106570 | ||||||
| Collection: | CaltechAUTHORS | ||||||
| Deposited By: | George Porter | ||||||
| Deposited On: | 10 Nov 2020 15:05 | ||||||
| Last Modified: | 10 Nov 2020 15:05 |
Repository Staff Only: item control page
