3 papers
cs.NI2026
Robust Lightweight IoT Device Fingerprinting Under Network Traffic Anomalies
Roya Taheri, Shamik Sengupta
Accurate IoT device identification is essential for network security, yet many existing approaches rely on payload inspection, feature engineering, or long observation windows that…
math-ph2026
Why we should condition denoising diffusion generative models on windows of past observations
Matthias Morzfeld, Daniel Hodyss
Data assimilation (DA) is, traditionally, a cycling process that relies on time-dependent priors to propagate information from past observations to future cycles. Using denoising d…
physics.ao-ph2025
Using Diffusion Models to do Data Assimilation
Daniel Hodyss, Matthias Morzfeld
The recent surge in machine learning (ML) methods for geophysical modeling has raised the question of how these methods might be applied to data assimilation (DA). We focus on diff…