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Hierarchical Bayesian Modelling for Knowledge Transfer Across Engineering Fleets via Multitask Learning. (arXiv:2204.12404v2 [stat.ML] UPDATED)
stat.ML updates on arXiv.org arxiv.org
A population-level analysis is proposed to address data sparsity when
building predictive models for engineering infrastructure. Utilising an
interpretable hierarchical Bayesian approach and operational fleet data, domain
expertise is naturally encoded (and appropriately shared) between different
sub-groups, representing (i) use-type, (ii) component, or (iii) operating
condition. Specifically, domain expertise is exploited to constrain the model
via assumptions (and prior distributions) allowing the methodology to
automatically share information between similar assets, improving the survival
analysis of a truck fleet and power …
arxiv bayesian engineering hierarchical knowledge learning ml modelling multitask learning transfer