11 citations as recorded by crossref.

1. Attractor learning in synchronized chaotic systems in the presence of unresolved scales W. Wiegerinck & F. Selten https://doi.org/10.1063/1.4990660
2. Implementation and validation of a supermodeling framework into Community Earth System Model version 2.1.5 W. Chapman et al. https://doi.org/10.5194/gmd-18-5451-2025
3. Integrated sea storm management strategy: the 29 October 2018 event in the Adriatic Sea C. Ferrarin et al. https://doi.org/10.5194/nhess-20-73-2020
4. Supermodeling in predictive diagnostics of cancer under treatment W. Dzwinel et al. https://doi.org/10.1016/j.compbiomed.2021.104797
5. Climate model tuning with adaptive supermodeling J. Seneca et al. https://doi.org/10.1063/5.0304768
6. Framework for an Ocean‐Connected Supermodel of the Earth System F. Counillon et al. https://doi.org/10.1029/2022MS003310
7. A Multi‐Model Ensemble Kalman Filter for Data Assimilation and Forecasting E. Bach & M. Ghil https://doi.org/10.1029/2022MS003123
8. Training a supermodel with noisy and sparse observations: a case study with CPT and the synch rule on SPEEDO – v.1 F. Schevenhoven & A. Carrassi https://doi.org/10.5194/gmd-15-3831-2022
9. Simulating climate with a synchronization-based supermodel F. Selten et al. https://doi.org/10.1063/1.4990721
10. Generalization properties of feed-forward neural networks trained on Lorenz systems S. Scher & G. Messori https://doi.org/10.5194/npg-26-381-2019
11. Improving weather and climate predictions by training of supermodels F. Schevenhoven et al. https://doi.org/10.5194/esd-10-789-2019