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20192025
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cs.LG2025

Noise Robust One-Class Intrusion Detection on Dynamic Graphs

Aleksei Liuliakov, Alexander Schulz, Luca Hermes +1

In the domain of network intrusion detection, robustness against contaminated and noisy data inputs remains a critical challenge. This study introduces a probabilistic version of t…

cs.LG2025

One-Class Intrusion Detection with Dynamic Graphs

Aleksei Liuliakov, Alexander Schulz, Luca Hermes +1

With the growing digitalization all over the globe, the relevance of network security becomes increasingly important. Machine learning-based intrusion detection constitutes a promi…

cs.LG2025

Conceptualizing Uncertainty: A Concept-based Approach to Explaining Uncertainty

Isaac Roberts, Alexander Schulz, Sarah Schroeder +2

Uncertainty in machine learning refers to the degree of confidence or lack thereof in a model's predictions. While uncertainty quantification methods exist, explanations of uncerta…

cs.LG2020

Reservoir memory machines

Benjamin Paassen, Alexander Schulz

In recent years, Neural Turing Machines have gathered attention by joining the flexibility of neural networks with the computational capabilities of Turing machines. However, Neura…

cs.LG2019

DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction

Alexander Schulz, Fabian Hinder, Barbara Hammer

Machine learning algorithms using deep architectures have been able to implement increasingly powerful and successful models. However, they also become increasingly more complex, m…