42 citations as recorded by crossref.

1. Data assimilation for heterogeneous networks: The consensus set T. Sauer & S. Schiff 10.1103/PhysRevE.79.051909
2. Data assimilation by delay‐coordinate nudging D. Pazó et al. 10.1002/qj.2732
3. Model and observation‐error covariance matrix information in the physical nudging equations G. Conti et al. 10.1002/qj.4979
4. Comment on “A unifying view of synchronization for data assimilation in complex nonlinear networks” [Chaos 27(12), 126802 (2017)] J. Tribbia 10.1063/1.5000522
5. The stability of adaptive synchronization of chaotic systems F. Sorrentino et al. 10.1063/1.3279646
6. Projected Shadowing-Based Data Assimilation B. de Leeuw et al. 10.1137/17M1141163
7. Analysis and computation of continuous data assimilation algorithms for Lorenz 63 system based on nonlinear nudging techniques Y. Du & M. Shiue 10.1016/j.cam.2020.113246
8. Effect of discrete time observations on synchronization in Chua model and applications to data assimilation M. Nurujjaman et al. 10.1063/1.4712591
9. Synchronicity from Synchronized Chaos G. Duane 10.3390/e17041701
10. Generalized synchronization and coherent structures in spatially extended systems L. Basnarkov et al. 10.1016/j.chaos.2013.11.007
11. Mathematical foundations of hybrid data assimilation from a synchronization perspective S. Penny 10.1063/1.5001819
12. Multi-Model Communication and Data Assimilation for Mitigating Model Error and Improving Forecasts Y. Chen & S. Stechmann 10.1007/s11401-019-0157-1
13. A multi-model ensemble method that combines imperfect models through learning L. van den Berge et al. 10.5194/esd-2-161-2011
14. A concept of a prognostic system for personalized anti-tumor therapy based on supermodeling W. Dzwinel et al. 10.1016/j.procs.2017.05.013
15. Exponential stability for a forecast-assimilation process with unstable dynamics D. Crisan et al. 10.1063/5.0241166
16. Towards model-based control of Parkinson's disease S. Schiff 10.1098/rsta.2010.0050
17. Estimation of communication-delays through adaptive synchronization of chaos F. Sorrentino & P. DeLellis 10.1016/j.chaos.2011.09.004
18. Dynamically combining climate models to “supermodel” the tropical Pacific M. Shen et al. 10.1002/2015GL066562
19. Synchronization of extended systems from internal coherence G. Duane 10.1103/PhysRevE.80.015202
20. Phase synchronization of baroclinic waves in a differentially heated rotating annulus experiment subject to periodic forcing with a variable duty cycle P. Read et al. 10.1063/1.5001817
21. Route to hyperchaos in a system of coupled oscillators with multistability N. McCullen & P. Moresco 10.1103/PhysRevE.83.046212
22. “FORCE” learning in recurrent neural networks as data assimilation G. Duane 10.1063/1.4990730
23. Analysis of parameter mismatches in the master stability function for network synchronization F. Sorrentino & M. Porfiri 10.1209/0295-5075/93/50002
24. Effects of density-affecting scalar on the onset of chaos in a simplified model of thermal convection: a nonlinear dynamical perspective S. Moon et al. 10.1140/epjp/s13360-020-01047-7
25. A Framework for Interpreting Regularized State Estimation N. Sugiura et al. 10.1175/MWR-D-12-00231.1
26. Efficient nonlinear data assimilation using synchronization in a particle filter F. Pinheiro et al. 10.1002/qj.3576
27. Simulating climate with a synchronization-based supermodel F. Selten et al. 10.1063/1.4990721
28. Synchronizing spatio-temporal chaos with imperfect models: A stochastic surface growth picture D. Pazó et al. 10.1063/1.4898385
29. A hybrid nudging‐ensemble Kalman filter approach to data assimilation in WRF/DART L. Lei et al. 10.1002/qj.1939
30. Attractor learning in synchronized chaotic systems in the presence of unresolved scales W. Wiegerinck & F. Selten 10.1063/1.4990660
31. An ensemble framework for time delay synchronization F. Pinheiro et al. 10.1002/qj.3204
32. Assimilation of ocean sea-surface height observations of mesoscale eddies J. Weiss & I. Grooms 10.1063/1.4986088
33. Complete synchronization of chaotic atmospheric models by connecting only a subset of state space P. Hiemstra et al. 10.5194/npg-19-611-2012
34. Introduction to focus issue: Synchronization in large networks and continuous media—data, models, and supermodels G. Duane et al. 10.1063/1.5018728
35. Data assimilation as a nonlinear dynamical systems problem: Stability and convergence of the prediction-assimilation system A. Carrassi et al. 10.1063/1.2909862
36. Mitigating Model Error via a Multimodel Method and Application to Tropical Intraseasonal Oscillations J. Torchinsky & S. Stechmann 10.1137/22M152551X
37. An efficient continuous data assimilation algorithm for the Sabra shell model of turbulence N. Chen et al. 10.1063/5.0057421
38. Supermodeling in Simulation of Melanoma Progression W. Dzwinel et al. 10.1016/j.procs.2016.05.396
39. Data assimilation in the geosciences: An overview of methods, issues, and perspectives A. Carrassi et al. 10.1002/wcc.535
40. On the problem of data assimilation by means of synchronization I. Szendro et al. 10.1029/2009JD012411
41. Asymptotic behavior of the forecast–assimilation process with unstable dynamics D. Crisan & M. Ghil 10.1063/5.0105590
42. Identical synchronization, with translation invariance, implies parameter estimation G. Duane et al. 10.1016/j.physleta.2007.06.059