9 citations as recorded by crossref.

1. A methodology to obtain model-error covariances due to the discretization scheme from the parametric Kalman filter perspective O. Pannekoucke et al.
2. Accurate deep learning-based filtering for chaotic dynamics by identifying instabilities without an ensemble M. Bocquet et al.
3. Covariance kernels investigation from diffusive wave equations for data assimilation in hydrology T. Malou & J. Monnier
4. PDE-NetGen 1.0: from symbolic partial differential equation (PDE) representations of physical processes to trainable neural network representations O. Pannekoucke & R. Fablet
5. Data assimilation using adaptive, non-conservative, moving mesh models A. Aydoğdu et al.
6. Exploring the limits of ensemble forecasting via solutions of the Liouville equation for realistic geophysical models A. Hermoso et al.
7. Continuum Covariance Propagation for Understanding Variance Loss in Advective Systems S. Gilpin et al.
8. Toward a multivariate formulation of the parametric Kalman filter assimilation: application to a simplified chemical transport model A. Perrot et al.
9. SymPKF (v1.0): a symbolic and computational toolbox for the design of parametric Kalman filter dynamics O. Pannekoucke & P. Arbogast