Data Assimilation: Methods, Algorithms, and Applications

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Disentangling Physical Dynamics From Unknown Factors for Unsupervised Video Prediction (2020, methodology): “PhyCell is based on a prediction-correction paradigm inspired from the data assimilation community [1], enabling robust training with missing data and for long-term forecasting.”
A consistent interpretation of the stochastic version of the Ensemble Kalman Filter (2020, background): “…Ensemble Kalman Filters or Smoothers (e.g., the discussion in van Leeuwen and Evensen, 1996, Gu and Oliver, 2007, Emerick and Reynolds, 2013, Asch et al., 2016), or explore transportation particle filters (e.g., Villani 2008, Reich, 2011, Liu and Wang, 2016, Pulido and van Leeuwen, 2019),…”
Data assimilation in the geosciences: An overview of methods, issues, and perspectives (2017, methodology): “This involves the storage of full covariance matrices, the derivation of the tangent linear model, and its application a number of times twice the state vector dimension (Asch et al., 2016).”