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Recommendations for the article Discovery of Physics From Data: Universal Laws and Discrepancies
Abstract | Title | Authors | Publication Date | Journal/ Conference | Citation count | Highest h-index |
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visibility_off | A Unified Sparse Optimization Framework to Learn Parsimonious Physics-Informed Models From Data | Kathleen P. Champion, P. Zheng, A. Aravkin, S. Brunton, J. Kutz | 2019-06-25 | IEEE Access | 107 | 68 |
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visibility_off | The Lie Detector. | A. Young, A. Lawrie | 2019-12-13 | arXiv: Signal Processing | 0 | 18 |
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visibility_off | Scale-invariant Learning by Physics Inversion | Philipp Holl, V. Koltun, Nils Thuerey | 2021-09-30 | ArXiv, DBLP | 6 | 106 |
visibility_off | Learning continuous models for continuous physics | A. Krishnapriyan, A. Queiruga, N. Benjamin Erichson, Michael W. Mahoney | 2022-02-17 | Communications Physics | 26 | 33 |
visibility_off | Machine Learning Conservation Laws from Trajectories. | Ziming Liu, Max Tegmark | 2021-05-06 | Physical review letters | 95 | 82 |
visibility_off | From data to conservation laws | F. Chirigati | 2023-09-01 | Nature Computational Science | 1 | 17 |
visibility_off | Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants | Liyao (Mars) Gao, J. Kutz | 2022-11-19 | Proceedings of the Royal Society A | 13 | 33 |
Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |