220 citations · 333 across the 8 of their papers we have counts for
5 papers · 1 filter
Group Pruning using a Bounded-Lp norm for Group Gating and Regularization
Chaithanya Kumar Mummadi, Tim Genewein, Dan Zhang +2
Deep neural networks achieve state-of-the-art results on several tasks while increasing in complexity. It has been shown that neural networks can be pruned during training by impos…
The streaming rollout of deep networks - towards fully model-parallel execution
Volker Fischer, Jan Köhler, Thomas Pfeil
Deep neural networks, and in particular recurrent networks, are promising candidates to control autonomous agents that interact in real-time with the physical world. However, this…
Universal Adversarial Perturbations Against Semantic Image Segmentation
Jan Hendrik Metzen, Mummadi Chaithanya Kumar, Thomas Brox +1
While deep learning is remarkably successful on perceptual tasks, it was also shown to be vulnerable to adversarial perturbations of the input. These perturbations denote noise add…
Adversarial Examples for Semantic Image Segmentation
Volker Fischer, Mummadi Chaithanya Kumar, Jan Hendrik Metzen +1
Machine learning methods in general and Deep Neural Networks in particular have shown to be vulnerable to adversarial perturbations. So far this phenomenon has mainly been studied…
On Detecting Adversarial Perturbations
Jan Hendrik Metzen, Tim Genewein, Volker Fischer +1
Machine learning and deep learning in particular has advanced tremendously on perceptual tasks in recent years. However, it remains vulnerable against adversarial perturbations of…