32 citations · 204 across the 33 of their papers we have counts for
5 papers · 1 filter
Adversarial Risk Bounds for Neural Networks through Sparsity based Compression
Emilio Rafael Balda, Arash Behboodi, Niklas Koep +1
Neural networks have been shown to be vulnerable against minor adversarial perturbations of their inputs, especially for high dimensional data under attacks. To comba…
A Deep Learning Wireless Transceiver with Fully Learned Modulation and Synchronization
Johannes Schmitz, Caspar von Lengerke, Nikita Airee +2
In this paper, we present a deep learning based wireless transceiver. We describe in detail the corresponding artificial neural network architecture, the training process, and repo…
Sensing Matrix Design and Sparse Recovery on the Sphere and the Rotation Group
Arya Bangun, Arash Behboodi, Rudolf Mathar
In this paper, {the goal is to design deterministic sampling patterns on the sphere and the rotation group} and, thereby, construct sensing matrices for sparse recovery of band-lim…
On the Effect of Low-Rank Weights on Adversarial Robustness of Neural Networks
Peter Langenberg, Emilio Rafael Balda, Arash Behboodi +1
Recently, there has been an abundance of works on designing Deep Neural Networks (DNNs) that are robust to adversarial examples. In particular, a central question is which features…
The Restricted Isometry Property of Block Diagonal Matrices for Group-Sparse Signal Recovery
Niklas Koep, Arash Behboodi, Rudolf Mathar
Group-sparsity is a common low-complexity signal model with widespread application across various domains of science and engineering. The recovery of such signal ensembles from com…