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Data assimilation, in its most comprehensive form, addresses the Bayesian inverse problem of identifying plausible state trajectories that explain noisy or incomplete observations of stochastic dynamical systems.
“Generative Modeling by Estimating Gradients of the Data Distribution”
Yang Song and Stefano Ermon · 1907
Earlier work this paper cites.
“A New Approach to Linear Filtering and Prediction Problems”
Rudolf. Kalman · 1960
Earlier work this paper cites.
“Deterministic Nonperiodic Flow”
Edward. Lorenz · 1963
Earlier work this paper cites.
“Correlation functions and computer simulations”
Giorgio Parisi · 1981
Earlier work this paper cites.
“Reverse-time diffusion equation models”
Brian Anderson · 1982
Earlier work this paper cites.
“Analysis methods for numerical weather prediction”
Andrew Lorenc · 1986
Earlier work this paper cites.
“Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects”
François-Xavier Le and Olivier Talagrand · 1986
Earlier work this paper cites.
“Novel approach to nonlinear/non-Gaussian Bayesian state estimation”
Neil Gordon et al · 1993
Earlier work this paper cites.
“Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics”
Geir Evensen · 1994
Earlier work this paper cites.
“Representations of Knowledge in Complex Systems”
Ulf Grenander and Michael. Miller · 1994
Earlier work this paper cites.
“Sequential Monte Carlo methods for dynamic systems”
Jun. Liu and Rong Chen · 1998
Earlier work this paper cites.
“The unscented Kalman filter for nonlinear estimation”
Eric. Wan and Rudolph Van · 2000
Earlier work this paper cites.
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Earlier work this paper cites.
“Accounting for an imperfect model in 4D-Var.”
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Laurent Girin et al · 2008
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Earlier work this paper cites.
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Ienkaran Arasaratnam and Simon Haykin · 2009
Earlier work this paper cites.
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Earlier work this paper cites.
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