42 citations · 60 across the 10 of their papers we have counts for
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cs.LG2019
Low Shot Learning with Untrained Neural Networks for Imaging Inverse Problems
Oscar Leong, Wesam Sakla
Employing deep neural networks as natural image priors to solve inverse problems either requires large amounts of data to sufficiently train expressive generative models or can suc…
cs.CV2019★ 42 cited
Invertible generative models for inverse problems: mitigating representation error and dataset bias
Muhammad Asim, Mara Daniels, Oscar Leong +2
Trained generative models have shown remarkable performance as priors for inverse problems in imaging -- for example, Generative Adversarial Network priors permit recovery of test…