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20222026
most citedPhysically recurrent neural networks for path-dependent heterogeneous materials: embedding constitutive models in a data-driven surrogate

81 citations · 87 across the 10 of their papers we have counts for

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Showing 2024 · physics.comp-phShow all

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physics.comp-ph2024

Integration of Active Learning and MCMC Sampling for Efficient Bayesian Calibration of Mechanical Properties

Leon Riccius, Iuri B. C. M. Rocha, Joris Bierkens +2

Recent advancements in Markov chain Monte Carlo (MCMC) sampling and surrogate modelling have significantly enhanced the feasibility of Bayesian analysis across engineering fields.…