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Recommendations for the article Physics-informed machine learning
| Abstract | Title | Authors | Publication Date | Journal/ Conference | Citation count | Highest h-index |
|---|---|---|---|---|---|---|
| visibility_off | A Taxonomic Survey of Physics-Informed Machine Learning | J. Pateras, P. Rana, Preetam Ghosh | 2023-06-07 | Applied Sciences | 7 | 11 |
| visibility_off | KoopmanLab: machine learning for solving complex physics equations | Wei Xiong, Muyuan Ma, Ziyang Zhang, Pei Sun, Yang Tian | 2023-01-03 | ArXiv | 7 | 6 |
| visibility_off | Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks and Operators in Scientific Computing: Fluid and Solid Mechanics | Salah A. Faroughi, Nikhil M. Pawar, Célio Fernandes, M. Raissi, Subasish Das, N. Kalantari, S. K. Mahjour | 2024-01-08 | J. Comput. Inf. Sci. Eng. | 22 | 24 |
| visibility_off | Machine Learning Through Physics–Informed Neural Networks: Progress and Challenges | Klapa Antonion, Xiao Wang, M. Raissi, Laurn Joshie | 2024-01-20 | Academic Journal of Science and Technology | 2 | 24 |
| visibility_off | Understanding on Physics-Informed DeepONet | Sang-Min Lee | 2024-01-31 | Journal of the Korea Academia-Industrial cooperation Society | 0 | 0 |
| visibility_off | Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing | Salah A. Faroughi, N. Pawar, C. Fernandes, Subasish Das, N. Kalantari, S. K. Mahjour | 2022-11-14 | ArXiv | 31 | 29 |
| visibility_off | Generic bounds on the approximation error for physics-informed (and) operator learning | Tim De Ryck, Siddhartha Mishra | 2022-05-23 | ArXiv | 48 | 10 |
| visibility_off | Scientific machine learning for closure models in multiscale problems: a review | Benjamin Sanderse, P. Stinis, R. Maulik, Shady E. Ahmed | 2024-03-05 | ArXiv | 4 | 21 |
| Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |