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A Meta-learning Formulation of the Autoencoder Problem for Non-linear Dimensionality Reduction
A rapidly growing area of research is the use of machine learning approaches such as autoencoders for dimensionality reduction of data and models in scientific applications.
Adjoint-Matching Neural Network Surrogates for Fast 4D-Var Data Assimilation
Surrogates constructed using adjoint information demonstrate superior performance on the 4D-Var data assimilation problem compared to a standard neural network surrogate that uses only forward dynamics information.
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