130 citations · 130 across the 3 of their papers we have counts for
4 papers
Geometric and Information Compression of Representations in Deep Learning
Linara Adilova, Henning Petzka, Asja Fischer +1
Deep neural networks transform input data into latent representations that support a wide range of downstream tasks. These representations can be characterized along information-th…
On the regularization of Wasserstein GANs
Henning Petzka, Asja Fischer, Denis Lukovnikov
Since their invention, generative adversarial networks (GANs) have become a popular approach for learning to model a distribution of real (unlabeled) data. Convergence problems dur…
PRADA: Probability-Ratio-Based Attribution and Detection of Autoregressive-Generated Images
Simon Damm, Jonas Ricker, Henning Petzka +1
Autoregressive (AR) image generation has recently emerged as a powerful paradigm for image synthesis. Leveraging the generation principle of large language models, they allow for e…
Flatness is Necessary, Neural Collapse is Not: Rethinking Generalization via Grokking
Ting Han, Linara Adilova, Henning Petzka +2
Neural collapse, i.e., the emergence of highly symmetric, class-wise clustered representations, is frequently observed in deep networks and is often assumed to reflect or enable ge…