pyWATTS: Python workflow automation tool for time series B Heidrich, A Bartschat, M Turowski, O Neumann, K Phipps, ... arXiv preprint arXiv:2106.10157, 2021 | 22 | 2021 |
Forecasting energy time series with profile neural networks B Heidrich, M Turowski, N Ludwig, R Mikut, V Hagenmeyer Proceedings of the eleventh acm international conference on future energy …, 2020 | 18 | 2020 |
Controlling non-stationarity and periodicities in time series generation using conditional invertible neural networks B Heidrich, M Turowski, K Phipps, K Schmieder, W Süß, R Mikut, ... Applied Intelligence 53 (8), 8826-8843, 2023 | 10 | 2023 |
Modeling and generating synthetic anomalies for energy and power time series M Turowski, M Weber, O Neumann, B Heidrich, K Phipps, HK Çakmak, ... Proceedings of the Thirteenth ACM International Conference on Future Energy …, 2022 | 9 | 2022 |
Enhancing anomaly detection methods for energy time series using latent space data representations M Turowski, B Heidrich, K Phipps, K Schmieder, O Neumann, R Mikut, ... Proceedings of the Thirteenth ACM International Conference on Future Energy …, 2022 | 5 | 2022 |
Towards line-restricted dispatchable feeders using probabilistic forecasts for PV-dominated low-voltage distribution grids D Werling, B Heidrich, HK Çakmak, V Hagenmeyer Proceedings of the Thirteenth ACM International Conference on Future Energy …, 2022 | 5 | 2022 |
Transformer training strategies for forecasting multiple load time series M Hertel, M Beichter, B Heidrich, O Neumann, B Schäfer, R Mikut, ... Energy Informatics 6 (Suppl 1), 20, 2023 | 3 | 2023 |
AutoPV: Automated photovoltaic forecasts with limited information using an ensemble of pre-trained models S Meisenbacher, B Heidrich, T Martin, R Mikut, V Hagenmeyer Proceedings of the 14th ACM International Conference on Future Energy …, 2023 | 3 | 2023 |
ProbPNN: Enhancing Deep Probabilistic Forecasting with Statistical Information B Heidrich, K Phipps, O Neumann, M Turowski, R Mikut, V Hagenmeyer arXiv preprint arXiv:2302.02597, 2023 | 3 | 2023 |
The impact of forecast characteristics on the forecast value for the dispatchable feeder D Werling, M Beichter, B Heidrich, K Phipps, R Mikut, V Hagenmeyer Companion Proceedings of the 14th ACM International Conference on Future …, 2023 | 2 | 2023 |
Creating probabilistic forecasts from arbitrary deterministic forecasts using conditional invertible neural networks K Phipps, B Heidrich, M Turowski, M Wittig, R Mikut, V Hagenmeyer arXiv preprint arXiv:2302.01800, 2023 | 2 | 2023 |
Boost short-term load forecasts with synthetic data from transferred latent space information B Heidrich, L Mannsperger, M Turowski, K Phipps, B Schäfer, R Mikut, ... Energy Informatics 5 (Suppl 1), 20, 2022 | 2 | 2022 |
Adaptively coping with concept drifts in energy time series forecasting using profiles B Heidrich, N Ludwig, M Turowski, R Mikut, V Hagenmeyer Proceedings of the Thirteenth ACM International Conference on Future Energy …, 2022 | 2 | 2022 |
Automating value-oriented forecast model selection by meta-learning: Application on a dispatchable feeder D Werling, M Beichter, B Heidrich, K Phipps, R Mikut, V Hagenmeyer Energy Informatics Academy Conference, 95-116, 2023 | 1 | 2023 |
Smart data representations: impact on the accuracy of deep neural networks O Neumann, N Ludwig, M Turowski, B Heidrich, V Hagenmeyer, R Mikut Proceedings 31 workshop computational intelligence, 113-130, 2021 | 1 | 2021 |
Generating probabilistic forecasts from arbitrary point forecasts using a conditional invertible neural network K Phipps, B Heidrich, M Turowski, M Wittig, R Mikut, V Hagenmeyer Applied Intelligence, 1-29, 2024 | | 2024 |
tsbootstrap: Enhancing Time Series Analysis with Advanced Bootstrapping Techniques S Gilda, B Heidrich, F Kiraly arXiv preprint arXiv:2404.15227, 2024 | | 2024 |
Using conditional Invertible Neural Networks to perform mid‐term peak load forecasting B Heidrich, M Hertel, O Neumann, V Hagenmeyer, R Mikut IET Smart Grid, 2024 | | 2024 |
Loss-Customised Probabilistic Energy Time Series Forecasts Using Automated Hyperparameter Optimisation K Phipps, S Meisenbacher, B Heidrich, M Turowski, R Mikut, ... Proceedings of the 14th ACM International Conference on Future Energy …, 2023 | | 2023 |
Automating day-ahead forecasting of photovoltaic power generation: Model design, monitoring, and adaption S Meisenbacher, T Martin, B Heidrich, R Mikut, V Hagenmeyer ETG Congress 2023, 1-8, 2023 | | 2023 |