3 papers
stat.ML2026
Unsupervised Domain Shift Detection with Interpretable Subspace Attribution
Sebastian Springer, Alessandro Laio
We developed a tool for detecting domain shifts, namely subtle differences in the probability distributions of datasets. We identify these shifts using an algorithm designed to det…
stat.ML2025
Detecting Localized Density Anomalies in Multivariate Data via Coin-Flip Statistics
Sebastian Springer, Andre Scaffidi, Maximilian Autenrieth +4
Detecting localized differences between two samples is a central task in scientific data analysis, required for the identification of signal events, regime changes, or model mismat…
physics.ao-ph2023
Agnostic detection of large-scale weather patterns in the northern hemisphere: from blockings to teleconnections
Sebastian Springer, Vera Melinda Galfi, Alessandro Laio +1
Detecting recurrent weather patterns and understanding the transitions between such regimes are key to advancing our knowledge on the low-frequency variability of the atmosphere an…