15 citations as recorded by crossref.

1. Bayesian inference of chaotic dynamics by merging data assimilation, machine learning and expectation-maximization M. Bocquet et al. https://doi.org/10.3934/fods.2020004
2. Computing Covariant Lyapunov Vectors in Hilbert spaces F. Noethen https://doi.org/10.3934/jcd.2021014
3. Second-order consistency for learning chaotic dynamics via randomized Jacobian matching S. Kang et al. https://doi.org/10.1063/5.0347780
4. Concept transfer of synaptic diversity from biological to artificial neural networks M. Hofmann et al. https://doi.org/10.1038/s41467-025-60078-9
5. Effective models and predictability of chaotic multiscale systems via machine learning F. Borra et al. https://doi.org/10.1103/PhysRevE.102.052203
6. Mechanics and thermodynamics of a new minimal model of the atmosphere G. Vissio & V. Lucarini https://doi.org/10.1140/epjp/s13360-020-00814-w
7. Data assimilation as a learning tool to infer ordinary differential equation representations of dynamical models M. Bocquet et al. https://doi.org/10.5194/npg-26-143-2019
8. Hamiltonian Lorenz-like models F. Fedele et al. https://doi.org/10.1016/j.physd.2024.134494
9. Analysis of a bistable climate toy model with physics-based machine learning methods M. Gelbrecht et al. https://doi.org/10.1140/epjs/s11734-021-00175-0
10. Online learning of both state and dynamics using ensemble Kalman filters M. Bocquet et al. https://doi.org/10.3934/fods.2020015
11. Detecting time-irreversibility in multiscale systems: Correlation and response functions in the Lorenz96 model N. Cocciaglia & D. Lucente https://doi.org/10.1063/5.0248658
12. Ultra-fast Unscented Kalman Inversion for the Calibration of Expensive Reduced Chaotic Models T. Price-Broncucia & R. Morrison https://doi.org/10.1137/25M1757290
13. Learning subgrid-scale models with neural ordinary differential equations S. Kang & E. Constantinescu https://doi.org/10.1016/j.compfluid.2023.105919
14. Heterogeneity of the attractor of the Lorenz ’96 model: Lyapunov analysis, unstable periodic orbits, and shadowing properties C. Maiocchi et al. https://doi.org/10.1016/j.physd.2023.133970
15. Multiscale Postprocessor for Ensemble Streamflow Prediction for Short to Long Ranges B. Alizadeh et al. https://doi.org/10.1175/JHM-D-19-0164.1