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Hyperparameter Estimation for Sparse Bayesian Learning Models
Sparse Bayesian Learning (SBL) models are extensively used in signal processing and machine learning for promoting sparsity through hierarchical priors.
Sequential edge detection using joint hierarchical Bayesian learning
This paper introduces a new sparse Bayesian learning (SBL) algorithm that jointly recovers a temporal sequence of edge maps from noisy and under-sampled Fourier data.
PCM-TV-TFV: A Novel Two Stage Framework for Image Reconstruction from Fourier Data
We propose in this paper a novel two-stage Projection Correction Modeling (PCM) framework for image reconstruction from (non-uniform) Fourier measurements.
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