3 papers
cs.LG2026
Evaluating Tabular Representation Learning for Network Intrusion Detection
Muhammad Usman Butt, Andreas Hotho, Daniel Schlör
Classic Network Intrusion Detection Systems (NIDS) often rely on manual feature engineering to extract meaningful patterns from network traffic data. However, this approach require…
cs.LG2025
Exploring Design Choices for Autoregressive Deep Learning Climate Models
Florian Gallusser, Simon Hentschel, Anna Krause +1
Deep Learning models have achieved state-of-the-art performance in medium-range weather prediction but often fail to maintain physically consistent rollouts beyond 14 days. In cont…
cs.LG2025
Physical knowledge improves prediction of EM Fields
Andrzej Dulny, Farzad Jabbarigargari, Andreas Hotho +3
We propose a 3D U-Net model to predict the spatial distribution of electromagnetic fields inside a radio-frequency (RF) coil with a subject present, using the phase, amplitude, and…