activity
20232026
most citedOML-AD: Online Machine Learning for Anomaly Detection in Time Series Data

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

math.PR2026

A Note on Physical Dependence and Mixing Conditions for Triangular Arrays

Florian Heinrichs

Under mild structural assumptions and regularity conditions on the marginal and conditional densities, an explicit bound on the -mixing coefficients in terms of the physical dep…

cs.LG2024★ 2 cited

OML-AD: Online Machine Learning for Anomaly Detection in Time Series Data

Sebastian Wette, Florian Heinrichs

Time series are ubiquitous and occur naturally in a variety of applications -- from data recorded by sensors in manufacturing processes, over financial data streams to climate data…

eess.SP2024

Detecting 5G Narrowband Jammers with CNN, k-nearest Neighbors, and Support Vector Machines

Matteo Varotto, Florian Heinrichs, Timo Schuerg +2

5G cellular networks are particularly vulnerable against narrowband jammers that target specific control sub-channels in the radio signal. One mitigation approach is to detect such…

stat.ML2024

GT-PCA: Effective and Interpretable Dimensionality Reduction with General Transform-Invariant Principal Component Analysis

Florian Heinrichs

Data analysis often requires methods that are invariant with respect to specific transformations, such as rotations in case of images or shifts in case of images and time series. W…

cs.LG2023★ 1 cited

Monitoring Machine Learning Models: Online Detection of Relevant Deviations

Florian Heinrichs

Machine learning models are essential tools in various domains, but their performance can degrade over time due to changes in data distribution or other factors. On one hand, detec…