OPTIMAL TRANSPORT, CYCLEGAN, AND PENALIZED LS FOR UNSUPERVISED LEARNING IN INVERSE PROBLEMS

no code implementations • 25 Sep 2019 • Byeongsu Sim, Gyutaek Oh, Sungjun Lim, and Jong Chul Ye

Specifically, we reveal that a cycleGAN architecture can be derived as a dual formulation of the optimal transport problem, if the PLS with a deep learning penalty is used as a transport cost between the two probability measures from measurements and unknown images.

Generative Adversarial Network