14 citations · 14 across the 3 of their papers we have counts for
3 papers
cs.AI2026
A Generalized Synthetic Control Method for Baseline Estimation in Demand Response Services
Jonas Sievers, Mardavij Roozbehani
Baseline estimation is critical to Demand Response (DR) settlement in electricity markets, yet existing machine learning methods remain limited in predictive performance, while met…
cs.LG2026
Knowledge Distillation for Efficient Transformer-Based Reinforcement Learning in Hardware-Constrained Energy Management Systems
Pascal Henrich, Jonas Sievers, Maximilian Beichter +3
Transformer-based reinforcement learning has emerged as a strong candidate for sequential control in residential energy management. In particular, the Decision Transformer can lear…
cs.LG2023★ 14 cited
Secure short-term load forecasting for smart grids with transformer-based federated learning
Jonas Sievers, Thomas Blank
Electricity load forecasting is an essential task within smart grids to assist demand and supply balance. While advanced deep learning models require large amounts of high-resoluti…