75 citations · 210 across the 10 of their papers we have counts for
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cs.LG2018
Variational Autoencoders Pursue PCA Directions (by Accident)
Michal Rolinek, Dominik Zietlow, Georg Martius
The Variational Autoencoder (VAE) is a powerful architecture capable of representation learning and generative modeling. When it comes to learning interpretable (disentangled) repr…
cs.LG2018★ 33 cited
L4: Practical loss-based stepsize adaptation for deep learning
Michal Rolinek, Georg Martius
We propose a stepsize adaptation scheme for stochastic gradient descent. It operates directly with the loss function and rescales the gradient in order to make fixed predicted prog…