Picard Proximal Monte Carlo for Parallel Bayesian Imaging with Score-Based Generative Priors
Bayesian imaging inverse problems often require sampling from high-dimensional posterior distributions. While recent score-based and diffusion models provide expressive Bayesian priors, their sampling procedures remain inherently sequential and computationally expensive for large-scale imaging applications. We propose...
Deliang Wei, Evan Bell, Wenhan Guo et al.
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