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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.…
stat.CO2024
Large sample scaling analysis of the Zig-Zag algorithm for Bayesian inference
Sanket Agrawal, Joris Bierkens, Gareth O. Roberts
Piecewise deterministic Markov processes provide scalable methods for sampling from the posterior distributions in big data settings by admitting principled sub-sampling strategies…