A determinant-free, gradient-based HMC sampler for fully Bayesian GPR that uses the pseudofermion trick and pole expansions to avoid the kernel determinant.
A randomized algorithm for approximating the log determinant of a symmetric positive definite matrix.Linear Algebra and its Applications, 533:95–117, November 2017
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A gradient-based and determinant-free framework for fully Bayesian Gaussian process regression
A determinant-free, gradient-based HMC sampler for fully Bayesian GPR that uses the pseudofermion trick and pole expansions to avoid the kernel determinant.