IEEE

Semi4TSF: End-to-End Semi-Supervised Contrastive Representation Learning for Time Series Forecasting

Abstract: Learning time series representations with sparse labels presents notable challenges. The surge in unsupervised contrastive learning has garnered increasing interest due to its immense ...
IEEE

Transformers for Multivariate Time Series Forecasting: Comprehensive Analysis, Challenges, Research Opportunities, and Future Prospects

Abstract: Multivariate time series (MTS) forecasting appears in many applied settings, ranging from finance and healthcare to energy systems, climate analysis, and IoT-based platforms. In these fields ...
The Lancet

AI-enabled forecasting of prehospital transfusion needs in patients with trauma: a multinational, registry-based, retrospective, machine learning development and validation study

aDepartment of Cardiology and Angiology, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany bUniversity Department of Anesthesiology and Intensive Care Medicine, ...