A hybridized MCMC framework performs trans-dimensional model selection and parameter estimation from sparse noisy data, recovering nuclear spin locations and couplings around spin defects with an order of magnitude less data than existing approaches.
Geological structure-guided 23 hybrid mcmc and bayesian linearized inversion methodology.Journal of Petroleum Science and Engineering, 199:108296
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Trans-dimensional Hamiltonian model selection and parameter estimation from sparse, noisy data
A hybridized MCMC framework performs trans-dimensional model selection and parameter estimation from sparse noisy data, recovering nuclear spin locations and couplings around spin defects with an order of magnitude less data than existing approaches.