Jonas Soenen

Semi-Supervised and Explainable Machine Learning with an Application to the Low-Voltage Grid

Estimating Dynamic Time Warping Distance Between Time Series with Missing Data

Measuring the Dissimilarity Between Time Series with Missing Data

Scenario generation of residential electricity consumption through sampling of historical data

AD-MERCS: Modeling Normality and Abnormality in Unsupervised Anomaly Detection

A scalable ensemble approach to forecast the electricity consumption of households

The effect of hyperparameter tuning on the comparative evaluation of unsupervised anomaly detection methods

Tackling noise in active semi-supervised clustering