Article

Discovering uncertainty: Bayesian constitutive artificial neural networks

2024-08-19

Abstract excerpt

Understanding uncertainty is critical, especially when data are sparse and variations are large. Bayesian neural networks offer a powerful strategy to build predictable models from sparse data, and inherently quantify both, aleatoric uncertainties of the data and epistemic uncertainties of the model. Yet, classical Bayesian neural networks ignore the fundamental laws of physics, they are non-interpretable, and the...

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Literature Corpus work: 7332b93e-dc72-500b-a83a-3f8b03cae521
DOI: 10.1101/2024.08.19.608595

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