3 papers
cs.HC2026
TSExplorer: An interactive data annotation and exploration tool for time-series data
Einari Vaaras, Manu Airaksinen, Okko Räsänen
We present TSExplorer, a cross-platform tool for interactive annotation and exploration of time-series data. The tool enables users to inspect high-dimensional datasets through mul…
cs.LG2026
Evaluating Interactive 2D Visualization as a Sample Selection Strategy for Biomedical Time-Series Data Annotation
Einari Vaaras, Manu Airaksinen, Okko Räsänen
Reliable machine-learning models in biomedical settings depend on accurate labels, yet annotating biomedical time-series data remains challenging. Algorithmic sample selection may…
cs.LG2025
Feature Space Topology Control via Hopkins Loss
Einari Vaaras, Manu Airaksinen
Feature space topology refers to the organization of samples within the feature space. Modifying this topology can be beneficial in machine learning applications, including dimensi…