70 citations · 196 across the 9 of their papers we have counts for
10 papers
Towards generalizing deep-audio fake detection networks
Konstantin Gasenzer, Moritz Wolter
Today's generative neural networks allow the creation of high-quality synthetic speech at scale. While we welcome the creative use of this new technology, we must also recognize th…
Canonical convolutional neural networks
Lokesh Veeramacheneni, Moritz Wolter, Reinhard Klein +1
We introduce canonical weight normalization for convolutional neural networks. Inspired by the canonical tensor decomposition, we express the weight tensors in so-called canonical…
Feature Selection on Quantum Computers
Sascha Mücke, Raoul Heese, Sabine Müller +2
In machine learning, fewer features reduce model complexity. Carefully assessing the influence of each input feature on the model quality is therefore a crucial preprocessing step.…
On the effects of biased quantum random numbers on the initialization of artificial neural networks
Raoul Heese, Moritz Wolter, Sascha Mücke +2
Recent advances in practical quantum computing have led to a variety of cloud-based quantum computing platforms that allow researchers to evaluate their algorithms on noisy interme…
Wavelet-Packets for Deepfake Image Analysis and Detection
Moritz Wolter, Felix Blanke, Raoul Heese +1
As neural networks become able to generate realistic artificial images, they have the potential to improve movies, music, video games and make the internet an even more creative an…
Quantum Circuit Evolution on NISQ Devices
Lukas Franken, Bogdan Georgiev, Sascha Mücke +4
Variational quantum circuits build the foundation for various classes of quantum algorithms. In a nutshell, the weights of a parametrized quantum circuit are varied until the empir…
Neural network compression via learnable wavelet transforms
Moritz Wolter, Shaohui Lin, Angela Yao
Wavelets are well known for data compression, yet have rarely been applied to the compression of neural networks. This paper shows how the fast wavelet transform can be used to com…
Unsupervised and Generic Short-Term Anticipation of Human Body Motions
Kristina Enes, Hassan Errami, Moritz Wolter +4
Various neural network based methods are capable of anticipating human body motions from data for a short period of time. What these methods lack are the interpretability and expla…
Sequence Prediction using Spectral RNNs
Moritz Wolter, Juergen Gall, Angela Yao
Fourier methods have a long and proven track record as an excellent tool in data processing. As memory and computational constraints gain importance in embedded and mobile applicat…
Complex Gated Recurrent Neural Networks
Moritz Wolter, Angela Yao
Complex numbers have long been favoured for digital signal processing, yet complex representations rarely appear in deep learning architectures. RNNs, widely used to process time s…