pyWATTS: Python workflow automation tool for time series B Heidrich, A Bartschat, M Turowski, O Neumann, K Phipps, ... arXiv preprint arXiv:2106.10157, 2021 | 23 | 2021 |

Automated annotator variability inspection for biomedical image segmentation MP Schilling, T Scherr, FR Münke, O Neumann, M Schutera, R Mikut, ... IEEE access 10, 2753-2765, 2022 | 17 | 2022 |

CoNIC Challenge: Pushing the frontiers of nuclear detection, segmentation, classification and counting S Graham, QD Vu, M Jahanifar, M Weigert, U Schmidt, W Zhang, J Zhang, ... Medical image analysis 92, 103047, 2024 | 12 | 2024 |

microbeSEG: A deep learning software tool with OMERO data management for efficient and accurate cell segmentation T Scherr, J Seiffarth, B Wollenhaupt, O Neumann, MP Schilling, ... Plos one 17 (11), e0277601, 2022 | 10* | 2022 |

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 | 10 | 2022 |

Ciscnet-a single-branch cell nucleus instance segmentation and classification network M Böhland, O Neumann, MP Schilling, M Reischl, R Mikut, K Löffler, ... 2022 IEEE International Symposium on Biomedical Imaging Challenges (ISBIC), 1-5, 2022 | 10* | 2022 |

On improving an already competitive segmentation algorithm for the Cell Tracking Challenge-lessons learned T Scherr, K Löffler, O Neumann, R Mikut bioRxiv, 2021.06. 26.450019, 2021 | 10 | 2021 |

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 | 6 | 2022 |

Evaluation of transformer architectures for electrical load time-series forecasting M Hertel, S Ott, B Schäfer, R Mikut, V Hagenmeyer, O Neumann Proceedings 32. Workshop Computational Intelligence 1, 93, 2022 | 5 | 2022 |

ObiWan-Microbi: OMERO-based integrated workflow for annotating microbes in the cloud J Seiffarth, T Scherr, B Wollenhaupt, O Neumann, H Scharr, D Kohlheyer, ... SoftwareX 26, 101638, 2024 | 4 | 2024 |

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 | 4 | 2023 |

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 |

A computational workflow for interdisciplinary deep learning projects utilizing bwHPC infrastructure MP Schilling, O Neumann, T Scherr, H Cui, AA Popova, PA Levkin, ... Proceedings of the 7th bwHPC Symposium 7, 69-74, 2022 | 3 | 2022 |

Transformer neural networks for building load forecasting M Hertel, S Ott, B Schäfer, R Mikut, V Hagenmeyer, O Neumann Tackling Climate Change with Machine Learning: Workshop at NeurIPS, 2022 | 3 | 2022 |

Using weather data in energy time series forecasting: the benefit of input data transformations O Neumann, M Turowski, R Mikut, V Hagenmeyer, N Ludwig Energy Informatics 6 (1), 44, 2023 | 2 | 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 | 2 | 2021 |

Managing Anomalies in Energy Time Series for Automated Forecasting M Turowski, O Neumann, L Mannsperger, K Kraus, K Layer, R Mikut, ... Energy Informatics Academy Conference, 3-29, 2023 | 1 | 2023 |

MLOps for Scarce Image Data: A Use Case in Microscopic Image Analysis AY Sitcheu, N Friederich, S Baeuerle, O Neumann, M Reischl, R Mikut Proceedings-33. Workshop Computational Intelligence: Berlin, 23.-24 …, 2023 | 1 | 2023 |

AI-based automated active learning for discovery of hidden dynamic processes: A use case in light microscopy N Friederich, AJ Yamachui Sitcheu, O Neumann, S Eroglu-Kayıkçı, ... Proceedings-33. Workshop Computational Intelligence: Berlin, 23.-24 …, 2023 | 1 | 2023 |

EasyMLServe: Easy deployment of REST machine learning services O Neumann, M Schilling, M Reischl, R Mikut PROCEEDINGS 32. WORKSHOP COMPUTATIONAL INTELLIGENCE 1, 11, 2022 | 1 | 2022 |