Online learning of both state and dynamics using ensemble Kalman filters
Marc Bocquet, Alban Farchi and Quentin Malartic

Iterative ensemble Kalman methods: A unified perspective with some new variants
Neil K. Chada, Yuming Chen and Daniel Sanz-Alonso

Ensemble Kalman Inversion for nonlinear problems: Weights, consistency, and variance bounds
Zhiyan Ding, Qin Li and Jianfeng Lu

An international initiative of predicting the SARS-CoV-2 pandemic using ensemble data assimilation 
Geir Evensen, Javier Amezcua, Marc Bocquet, Alberto Carrassi, Alban Farchi, Alison Fowler, Pieter L. Houtekamer, Christopher K. Jones, Rafael J. de Moraes, Manuel Pulido, Christian Sampson and Femke C. Vossepoel

A study of disproportionately affected populations by race/ethnicity during the SARS-CoV-2 pandemic using multi-population SEIR modeling and ensemble data assimilation
Emmanuel Fleurantin, Christian Sampson, Daniel Paul Maes, Justin Bennett, Tayler Fernandes-Nunez, Sophia Marx and Geir Evensen

Feedback particle filter for collective inference
Jin-Won Kim, Amirhossein Taghvaei, Yongxin Chen and Prashant G. Mehta

Mean field limit of Ensemble Square Root filters-discrete and continuous time
Theresa Lange and Wilhelm Stannat

A surrogate-based approach to nonlinear, non-Gaussian joint state-parameter data assimilation
John Maclean and Elaine T. Spiller

Analysis of the feedback particle filter with diffusion map based approximation of the gain
Sahani Pathiraja and Wilhelm Stannat

Stability of non-linear filter for deterministic dynamics
Anugu Sumith Reddy and Amit Apte