Shallow Recurrent Decoders map point-kinetics time series to multi-group diffusion solutions on a benchmark reactor geometry.
and Braghin, Francesco and Manzoni, Andrea and Kutz, J
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Bayesian-ARGOS is a hybrid frequentist-Bayesian method that discovers equations from limited noisy observations more efficiently than SINDy or bootstrap-ARGOS while adding uncertainty quantification.
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Multi-Fidelity Learning with Shallow Recurrent Decoders for Reactor Physics
Shallow Recurrent Decoders map point-kinetics time series to multi-group diffusion solutions on a benchmark reactor geometry.
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Fast and principled equation discovery from chaos to climate
Bayesian-ARGOS is a hybrid frequentist-Bayesian method that discovers equations from limited noisy observations more efficiently than SINDy or bootstrap-ARGOS while adding uncertainty quantification.