most citedCombating Mode Collapse in GAN training: An Empirical Analysis using Hessian Eigenvalues

2 citations · 2 across the 2 of their papers we have counts for

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2 papers

cs.LG2020★ 2 cited

Combating Mode Collapse in GAN training: An Empirical Analysis using Hessian Eigenvalues

Ricard Durall, Avraam Chatzimichailidis, Peter Labus +1

Generative adversarial networks (GANs) provide state-of-the-art results in image generation. However, despite being so powerful, they still remain very challenging to train. This i…

cs.LG2019

GradVis: Visualization and Second Order Analysis of Optimization Surfaces during the Training of Deep Neural Networks

Avraam Chatzimichailidis, Franz-Josef Pfreundt, Nicolas R. Gauger +1

Current training methods for deep neural networks boil down to very high dimensional and non-convex optimization problems which are usually solved by a wide range of stochastic gra…