| Short-term density forecasting of low-voltage load using Bernstein-polynomial normalizing flows M Arpogaus, M Voss, B Sick, M Nigge-Uricher, O Dürr IEEE Transactions on Smart Grid 14 (6), 4902-4911, 2023 | 20 | 2023 |
| Probabilistic short-term low-voltage load forecasting using bernstein-polynomial normalizing flows M Arpogaus, M Voß, B Sick, M Nigge-Uricher, O Dürr ICML 2021, Workshop Tackling Climate Change with Machine Learning, June 26 …, 2021 | 14 | 2021 |
| How Inverse Conditional Flows Can Serve as a Substitute for Distributional Regression L Kook, C Kolb, P Schiele, D Dold, M Arpogaus, C Fritz, PF Baumann, ... arXiv preprint arXiv:2405.05429, 2024 | 1 | 2024 |
| Probabilistic real-time grid operation management of future distribution grids with high penetration of renewable generators and electrical vehicles based on artificial … M Arpogaus, J Montalbano, M Linke, G Schubert CIRED Porto Workshop 2022: E-mobility and power distribution systems, 147-151, 2022 | 1 | 2022 |
| Probabilistic Short-Term Load Forecasting using conditioned normalizing flows M Arpogaus | 1 | 2020 |
| 2023 Index IEEE Transactions on Smart Grid Vol. 14 A Abazari, AO Abbas, A Abbaspour, AA Abdalla, J Abdella, AR Abhyankar, ... IEEE Transactions on Smart Grid 14 (6), 2023 | | 2023 |
Oliver DürrProfessor of Data Science, Konstanz University of Applied SciencesBestätigte E-Mail-Adresse bei htwg-konstanz.de
