Corpus ID: 155100232

Deep Compressed Sensing

@inproceedings{Wu2019DeepCS,
  title={Deep Compressed Sensing},
  author={Yan Jennifer Wu and Mihaela Rosca and Timothy P. Lillicrap},
  booktitle={ICML},
  year={2019}
}
  • Yan Jennifer Wu, Mihaela Rosca, Timothy P. Lillicrap
  • Published in ICML 2019
  • Mathematics, Computer Science, Engineering
  • Compressed sensing (CS) provides an elegant framework for recovering sparse signals from compressed measurements. For example, CS can exploit the structure of natural images and recover an image from only a few random measurements. CS is flexible and data efficient, but its application has been restricted by the strong assumption of sparsity and costly reconstruction process. A recent approach that combines CS with neural network generators has removed the constraint of sparsity, but… CONTINUE READING

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