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Recommendations for the article Chaos as an intermittently forced linear system
| Abstract | Title | Authors | Publication Date | Journal/ Conference | Citation count | Highest h-index |
|---|---|---|---|---|---|---|
| visibility_off | Featurizing Koopman mode decomposition for robust forecasting | D. Aristoff, J. Copperman, Nathan Mankovich, Alexander Davies | 2023-12-14 | The Journal of Chemical Physics | 0 | 12 |
| visibility_off | Deep learning delay coordinate dynamics for chaotic attractors from partial observable data | Charles D. Young, M. Graham | 2022-11-20 | Physical review. E | 9 | 51 |
| visibility_off | DEFM: Delay-embedding-based forecast machine for time series forecasting by spatiotemporal information transformation. | Hao Peng, Pei Chen, R. Liu | 2020-05-16 | Chaos | 1 | 80 |
| visibility_off | DEFM: Delay-embedding-based forecast machine for time series forecasting by spatiotemporal information transformation. | Hao Peng, Pei Chen, R. Liu | 2020-05-16 | Chaos | 1 | 80 |
| visibility_off | Detecting chaos in lineage-trees: A deep learning approach | H. Rappeport, Irit Levin Reisman, Naftali Tishby, N. Balaban | 2021-06-08 | ArXiv | 3 | 56 |
| visibility_off | Cluster-based network modeling—From snapshots to complex dynamical systems | Daniel Fernex, B. R. Noack, R. Semaan | 2021-06-01 | Science Advances | 44 | 49 |
| visibility_off | Cluster-based network modeling -- automated robust modeling of complex dynamical systems | Daniel Fernex, B. R. Noack, R. Semaan | 2020-10-30 | arXiv: Data Analysis, Statistics and Probability | 1 | 49 |
| Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |