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Found 3 papers, 1 papers with code
Learning Fourier-Constrained Diffusion Bridges for MRI Reconstruction
Instead of the target transformation from undersampled to fully-sampled data required for MRI reconstruction, common diffusion priors are trained to learn a task-agnostic transformation from an asymptotic start-point of Gaussian noise onto the finite end-point of fully-sampled data.
Comments on "Deep Neural Networks with Random Gaussian Weights: A Universal Classification Strategy?"
In a recently published paper [1], it is shown that deep neural networks (DNNs) with random Gaussian weights preserve the metric structure of the data, with the property that the distance shrinks more when the angle between the two data points is smaller.
Statistically Segregated k-Space Sampling for Accelerating Multiple-Acquisition MRI
To address this problem, a statistically-segregated sampling method is proposed for multiple-acquisition MRI.
Image and Video Processing
