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math.NA2026
Efficient sampling for sparse Bayesian learning using hierarchical prior normalization
Jan Glaubitz, Youssef Marzouk
We introduce an approach for efficient Markov chain Monte Carlo (MCMC) sampling for challenging high-dimensional distributions in sparse Bayesian learning (SBL). The core innovatio…
math.NA2026
Optimizing Irreversible Perturbations of the Unadjusted Langevin Algorithm
Qianyu Julie Zhu, Youssef Marzouk, Konstantinos Spiliopoulos +1
Irreversible perturbations accelerate the convergence of Langevin dynamics, breaking detailed balance while preserving the invariant measure. The design of optimal irreversible per…
math.NA2025
Priorconditioned Sparsity-Promoting Projection Methods for Deterministic and Bayesian Linear Inverse Problems
Jonathan Lindbloom, Mirjeta Pasha, Jan Glaubitz +1
High-quality reconstructions of signals and images with sharp edges are needed in a wide range of applications. To overcome the large dimensionality of the parameter space and the…