5 citations · 5 across the 1 of their papers we have counts for
2 papers
cs.LG2021★ 5 cited
On Characterizing GAN Convergence Through Proximal Duality Gap
Sahil Sidheekh, Aroof Aimen, Narayanan C. Krishnan
Despite the accomplishments of Generative Adversarial Networks (GANs) in modeling data distributions, training them remains a challenging task. A contributing factor to this diffic…
cs.LG2020
On Duality Gap as a Measure for Monitoring GAN Training
Sahil Sidheekh, Aroof Aimen, Vineet Madan +1
Generative adversarial network (GAN) is among the most popular deep learning models for learning complex data distributions. However, training a GAN is known to be a challenging ta…