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Data assimilation into physics-based thermoacoustic models using Bayesian neural network ensembles

Croci, Maximilian LouisUniversity of Cambridge2022

… proposed, which uses a heteroscedastic Bayesian neural network ensemble (BayNNE) trained on a library of simulated flame fronts with known parameters to infer the parameters and uncertainties of the physics-based model. Generating the library of simulated flame fronts and training the BayNNE on …

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Ensemble methods for spatial data stream classification with application to emergency services

Bhattacharjee, Prasanta, University of Lethbridge. Faculty of Arts and Science2024

lethbridge