1 citations · 1 across the 3 of their papers we have counts for
3 papers
Model-adapted Fourier sampling for generative compressed sensing
Aaron Berk, Simone Brugiapaglia, Yaniv Plan +3
We study generative compressed sensing when the measurement matrix is randomly subsampled from a unitary matrix (with the DFT as an important special case). It was recently shown t…
Learning from few examples: Classifying sex from retinal images via deep learning
Aaron Berk, Gulcenur Ozturan, Parsa Delavari +3
Deep learning has seen tremendous interest in medical imaging, particularly in the use of convolutional neural networks (CNNs) for developing automated diagnostic tools. The facili…
A coherence parameter characterizing generative compressed sensing with Fourier measurements
Aaron Berk, Simone Brugiapaglia, Babhru Joshi +3
In Bora et al. (2017), a mathematical framework was developed for compressed sensing guarantees in the setting where the measurement matrix is Gaussian and the signal structure is…