This page was last updated on 2025-03-03 06:06:16 UTC
Recommendations for the article Learning Discrepancy Models From Experimental Data
| Abstract | Title | Authors | Publication Date | Journal/ Conference | Citation count | Highest h-index |
|---|---|---|---|---|---|---|
| visibility_off | Sparse identification of Lagrangian for nonlinear dynamical systems via proximal gradient method | Adam Purnomo, M. Hayashibe | 2022-09-04 | Scientific Reports | 4 | 25 |
| visibility_off | SINDy vs Hard Nonlinearities and Hidden Dynamics: a Benchmarking Study | Aurelio Raffa Ugolini, Valentina Breschi, Andrea Manzoni, M. Tanelli | 2024-03-01 | ArXiv | 1 | 2 |
| visibility_off | Machine Learning and System Identification for Estimation in Physical Systems | Fredrik Bagge Carlson | 2018-12-20 | ArXiv | 5 | 8 |
| visibility_off | Composed Physics- and Data-driven System Identification for Non-autonomous Systems in Control Engineering | Ricarda-Samantha Götte, Julia Timmermann | 2021-12-15 | 2022 3rd International Conference on Artificial Intelligence, Robotics and Control (AIRC) | 5 | 5 |
| visibility_off | Sparse identification of nonlinear dynamics for model predictive control in the low-data limit | E. Kaiser, J. Kutz, S. Brunton | 2017-11-15 | Proceedings. Mathematical, Physical, and Engineering Sciences | 488 | 68 |
| visibility_off | Data-based modeling and control of nonlinear process systems using sparse identification: An overview of recent results | Fahim Abdullah, P. Christofides | 2023-03-01 | Comput. Chem. Eng. | 19 | 77 |
| visibility_off | SINDy-PI: a robust algorithm for parallel implicit sparse identification of nonlinear dynamics | Kadierdan Kaheman, J. Kutz, S. Brunton | 2020-04-05 | Proceedings. Mathematical, Physical, and Engineering Sciences | 238 | 68 |
| Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |