Benedikt Heidrich

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 19

Top Topics

Data Representation

Weather Forecasting

Top Venues

Publications

Kaleb Phipps, Benedikt Heidrich, Marian Turowski, Moritz Wittig, Ralf Mikut, Veit Hagenmeyer
Generating probabilistic forecasts from arbitrary point forecasts using a conditional invertible neural network. Appl. Intell. 54 (8) (2024)
Kaleb Phipps, Stefan Meisenbacher, Benedikt Heidrich, Marian Turowski, Ralf Mikut, Veit Hagenmeyer
Loss-Customised Probabilistic Energy Time Series Forecasts Using Automated Hyperparameter Optimisation. e-Energy (2023)
Matthias Hertel, Maximilian Beichter, Benedikt Heidrich, Oliver Neumann, Benjamin Schäfer, Ralf Mikut, Veit Hagenmeyer
Transformer training strategies for forecasting multiple load time series. Energy Inform. 6 (1) (2023)
Kaleb Phipps, Benedikt Heidrich, Marian Turowski, Moritz Wittig, Ralf Mikut, Veit Hagenmeyer
Creating Probabilistic Forecasts from Arbitrary Deterministic Forecasts using Conditional Invertible Neural Networks. CoRR (2023)
Stefan Meisenbacher, Benedikt Heidrich, Tim Martin, Ralf Mikut, Veit Hagenmeyer
AutoPV: Automated photovoltaic forecasts with limited information using an ensemble of pre-trained models. e-Energy (2023)
Benedikt Heidrich, Marian Turowski, Kaleb Phipps, Kai Schmieder, Wolfgang Süß, Ralf Mikut, Veit Hagenmeyer
Controlling non-stationarity and periodicities in time series generation using conditional invertible neural networks. Appl. Intell. 53 (8) (2023)
Benedikt Heidrich, Kaleb Phipps, Oliver Neumann, Marian Turowski, Ralf Mikut, Veit Hagenmeyer
ProbPNN: Enhancing Deep Probabilistic Forecasting with Statistical Information. CoRR (2023)
Dorina Werling, Maximilian Beichter, Benedikt Heidrich, Kaleb Phipps, Ralf Mikut, Veit Hagenmeyer
The Impact of Forecast Characteristics on the Forecast Value for the Dispatchable Feeder. e-Energy (Companion) (2023)
Dorina Werling, Maximilian Beichter, Benedikt Heidrich, Kaleb Phipps, Ralf Mikut, Veit Hagenmeyer
Automating Value-Oriented Forecast Model Selection by Meta-learning: Application on a Dispatchable Feeder. EI.A (2023)
Matthias Hertel, Maximilian Beichter, Benedikt Heidrich, Oliver Neumann, Benjamin Schäfer, Ralf Mikut, Veit Hagenmeyer
Transformer Training Strategies for Forecasting Multiple Load Time Series. CoRR (2023)
Dorina Werling, Benedikt Heidrich, Hüseyin Kemâl Çakmak, Veit Hagenmeyer
Towards line-restricted dispatchable feeders using probabilistic forecasts for PV-dominated low-voltage distribution grids. e-Energy (2022)
Benedikt Heidrich, Lisa Mannsperger, Marian Turowski, Kaleb Phipps, Benjamin Schäfer, Ralf Mikut, Veit Hagenmeyer
Boost short-term load forecasts with synthetic data from transferred latent space information. Energy Inform. 5 (2022)
Stefan Meisenbacher, Benedikt Heidrich, Tim Martin, Ralf Mikut, Veit Hagenmeyer
AutoPV: Automated photovoltaic forecasts with limited information using an ensemble of pre-trained models. CoRR (2022)
Marian Turowski, Moritz Weber, Oliver Neumann, Benedikt Heidrich, Kaleb Phipps, Hüseyin Kemâl Çakmak, Ralf Mikut, Veit Hagenmeyer
Modeling and generating synthetic anomalies for energy and power time series. e-Energy (2022)
Benedikt Heidrich, Nicole Ludwig, Marian Turowski, Ralf Mikut, Veit Hagenmeyer
Adaptively coping with concept drifts in energy time series forecasting using profiles. e-Energy (2022)
Marian Turowski, Benedikt Heidrich, Kaleb Phipps, Kai Schmieder, Oliver Neumann, Ralf Mikut, Veit Hagenmeyer
Enhancing anomaly detection methods for energy time series using latent space data representations. e-Energy (2022)
Benedikt Heidrich, Andreas Bartschat, Marian Turowski, Oliver Neumann, Kaleb Phipps, Stefan Meisenbacher, Kai Schmieder, Nicole Ludwig, Ralf Mikut, Veit Hagenmeyer
pyWATTS: Python Workflow Automation Tool for Time Series. CoRR (2021)
Oliver Neumann, Nicole Ludwig, Marian Turowski, Benedikt Heidrich, Veit Hagenmeyer, Ralf Mikut
Smart Data Representations: Impact on the Accuracy of Deep Neural Networks. CoRR (2021)
Benedikt Heidrich, Marian Turowski, Nicole Ludwig, Ralf Mikut, Veit Hagenmeyer
Forecasting energy time series with profile neural networks. e-Energy (2020)