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Bayesian Model Selection of Lithium-Ion Battery Models via Bayesian Quadrature. (arXiv:2210.17299v3 [stat.ME] UPDATED)
Nov. 15, 2022, 2:13 a.m. | Masaki Adachi, Yannick Kuhn, Birger Horstmann, Arnulf Latz, Michael A. Osborne, David A. Howey
cs.LG updates on arXiv.org arxiv.org
A wide variety of battery models are available, and it is not always obvious
which model `best' describes a dataset. This paper presents a Bayesian model
selection approach using Bayesian quadrature. The model evidence is adopted as
the selection metric, choosing the simplest model that describes the data, in
the spirit of Occam's razor. However, estimating this requires integral
computations over parameter space, which is usually prohibitively expensive.
Bayesian quadrature offers sample-efficient integration via model-based
inference that minimises the number …
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