1.7k citations · 2.4k across the 47 of their papers we have counts for
51 papers
Does Your Model Think Like an Engineer? Explainable AI for Bearing Fault Detection with Deep Learning
Thomas Decker, Michael Lebacher, Volker Tresp
Deep Learning has already been successfully applied to analyze industrial sensor data in a variety of relevant use cases. However, the opaque nature of many well-performing methods…
Differentiable Quantum Architecture Search for Quantum Reinforcement Learning
Yize Sun, Yunpu Ma, Volker Tresp
Differentiable quantum architecture search (DQAS) is a gradient-based framework to design quantum circuits automatically in the NISQ era. It was motivated by such as low fidelity o…
Adversarial Examples on Segmentation Models Can be Easy to Transfer
Jindong Gu, Hengshuang Zhao, Volker Tresp +1
Deep neural network-based image classification can be misled by adversarial examples with small and quasi-imperceptible perturbations. Furthermore, the adversarial examples created…
Are Vision Transformers Robust to Patch Perturbations?
Jindong Gu, Volker Tresp, Yao Qin
Recent advances in Vision Transformer (ViT) have demonstrated its impressive performance in image classification, which makes it a promising alternative to Convolutional Neural Net…
Categorical EHR Imputation with Generative Adversarial Nets
Yinchong Yang, Zhiliang Wu, Volker Tresp +1
Electronic Health Records often suffer from missing data, which poses a major problem in clinical practice and clinical studies. A novel approach for dealing with missing data are…
Few-Shot One-Class Classification via Meta-Learning
Ahmed Frikha, Denis Krompaß, Hans-Georg Köpken +1
Although few-shot learning and one-class classification (OCC), i.e., learning a binary classifier with data from only one class, have been separately well studied, their intersecti…