Publications

The impact of heat pumps on day-ahead energy community load forecasting
Semmelmann, L.; Hertel, M.; Kircher, K. J.; Mikut, R.; Hagenmeyer, V.; Weinhardt, C.
2024. Applied Energy, 368, 123364. doi:10.1016/j.apenergy.2024.123364

Feasibility of Forecasting Highly Resolved Power Grid Frequency Utilizing Temporal Fusion Transformers
Pütz, S.; El Ashhab, H.; Hertel, M.; Mikut, R.; Götz, M.; Hagenmeyer, V.; Schäfer, B.
2024. e-Energy ’24: Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems, 447–453, Association for Computing Machinery (ACM). doi:10.1145/3632775.3661963

AI serving grid stability: detecting anomalies in automatic frequency restoration data
Beichter, M.; Hertel, M.; Hülsen, H. von; Oberhofer, U.; Pütz, S.
2024, February 14. Hessian.AI Industry Challenge Final Event (2024), Online, February 13–14, 2024

Explainability and Benchmarking of Transformers for Time-Series Forecasting
Hertel, M.; Pütz, S.; Schäfer, B.; Mikut, R.; Hagenmeyer, V.
2024. Helmholtz Artificial Intelligence Conference (Helmholtz AI 2024), Düsseldorf, Germany, June 12–14, 2024

Using conditional Invertible Neural Networks to perform mid‐term peak load forecasting
Heidrich, B.; Hertel, M.; Neumann, O.; Hagenmeyer, V.; Mikut, R.
2024. IET Smart Grid. doi:10.1049/stg2.12169

A Fair and In-Depth Evaluation of Existing End-to-End Entity Linking Systems
Bast, H.; Hertel, M.; Prange, N.
2023. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, Singapur, 6th-10th December 2023, Hrsg.: Bouamor, Houda; Pino, Juan; Bali, Kalika, 6659–6672, Association for Computational Linguistics (ACL). doi:10.18653/v1/2023.emnlp-main.411

Transformer training strategies for forecasting multiple load time series
Hertel, M.; Beichter, M.; Heidrich, B.; Neumann, O.; Schäfer, B.; Mikut, R.; Hagenmeyer, V.
2023. Energy Informatics, 6 (S1), Art.-Nr.: 20. doi:10.1186/s42162-023-00278-z

Fast Whitespace Correction with Encoder-Only Transformers
Bast, H.; Hertel, M.; Walter, S.
2023. The 61st Annual Meeting of the Association for Computational Linguistics: System Demonstrations : ACL-DEMO 2023. Vol 3: Proceedings of the System Demonstrations, 389–399, Association for Computational Linguistics (ACL). doi:10.18653/v1/2023.acl-demo.37

Using Conditional Invertible Neural Networks To Perform Mid-Term Peak Load Forecasting
Heidrich, B.; Neumann, O.; Hertel, M.; Hagenmeyer, V.; Mikut, R.
2023. 43rd International Symposium On Forecasting (2023), Charlottesville, VA, USA, June 25–28, 2023

Winning the Peak Shape and Peak Timing Tasks of the BIGDEAL Load Forecasting Challenge with Conditional Invertible Neural Networks
Neumann, O.; Heidrich, B.; Hertel, M.; Hagenmeyer, V.; Mikut, R.
2023. Helmholtz Artificial Intelligence Conference (Helmholtz AI 2023), Hamburg, Germany, June 12–14, 2023

Electrical Load Forecasting with Transformer Neural Networks
Hertel, M.; Beichter, M.; Heidrich, B.; Neumann, O.; Ott, S. M.; Schäfer, B.; Mikut, R.; Hagenmeyer, V.
2023. Helmholtz Artificial Intelligence Conference (Helmholtz AI 2023), Hamburg, Germany, June 12–14, 2023

Transformer Neural Networks for Building Load Forecasting
Hertel, M.; Ott, S.; Neumann, O.; Schäfer, B.; Mikut, R.; Hagenmeyer, V.
2022. 36th Conference on Neural Information Processing Systems (NeurIPS 2022), Online, November 28–December 9, 2022

Evaluation of Transformer Architectures for Electrical Load Time-Series Forecasting
Hertel, M.; Ott, S.; Schäfer, B.; Mikut, R.; Hagenmeyer, V.; Neumann, O.
2022. Proceedings - 32. Workshop Computational Intelligence: Berlin, 1. - 2. Dezember 2022. Hrsg.: H. Schulte, F. Hoffmann; R. Mikut, 93–110, KIT Scientific Publishing