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Theory of GANs for Compressed Sensing

Online lecture on Theory for GAN priors in Compressed Sensing. This lecture is from Northeastern University's CS 7180 Spring 2020 class on Special Topics in Artificial Intelligence, taught by Paul Hand.

The notes are available at:
http://khoury.northeastern.edu/home/hand/teaching/cs7180-spring-2020/lecture10-GANS-for-compressed-sensing.pdf

The papers mentioned:
Bora, Ashish, Ajil Jalal, Eric Price, and Alexandros G. Dimakis. "Compressed sensing using generative models." In Proceedings of the 34th International Conference on Machine Learning-Volume 70, pp. 537-546. JMLR. org, 2017. https://arxiv.org/abs/1703.03208

Hand, Paul, and Vladislav Voroninski. "Global guarantees for enforcing deep generative priors by empirical risk." IEEE Transactions on Information Theory 66.1 (2019): 401-418. https://arxiv.org/abs/1705.07576

Huang, Wen, Paul Hand, Reinhard Heckel, and Vladislav Voroninski. "A provably convergent scheme for compressive sensing under random generative priors." arXiv preprint arXiv:1812.04176 (2018).

Видео Theory of GANs for Compressed Sensing канала Paul Hand
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20 марта 2020 г. 4:54:04
00:57:02
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