| Review of automated time series forecasting pipelines S Meisenbacher, M Turowski, K Phipps, M Rätz, D Müller, V Hagenmeyer, ... Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 12 (6 …, 2022 | 32 | 2022 |
| Vertical Scaling Capability of OpenStack: Survey of Guest Operating Systems, Hypervisors, and the Cloud Management Platform M Turowski, A Lenk Service-Oriented Computing-ICSOC 2014 Workshops: WESOA; SeMaPS, RMSOC, KASA …, 2015 | 26 | 2015 |
| Data-Driven Copy-Paste Imputation for Energy Time Series M Weber, M Turowski, HK Çakmak, R Mikut, U Kühnapfel, V Hagenmeyer IEEE Transactions on Smart Grid 12 (6), 5409-5419, 2021 | 24 | 2021 |
| pyWATTS: Python workflow automation tool for time series B Heidrich, A Bartschat, M Turowski, O Neumann, K Phipps, ... arXiv preprint arXiv:2106.10157, 2021 | 21 | 2021 |
| Forecasting energy time series with profile neural networks B Heidrich, M Turowski, N Ludwig, R Mikut, V Hagenmeyer Proceedings of the Elventh ACM International Conference on Future Energy …, 2020 | 17 | 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 | 8 | 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 | 8 | 2022 |
| Point and contextual anomaly detection in building load profiles of a university campus L Wang, M Turowski, M Zhang, T Riedel, M Beigl, R Mikut, V Hagenmeyer 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), 11-15, 2020 | 7 | 2020 |
| ALDI++: Automatic and parameter-less discord and outlier detection for building energy load profiles M Quintana, T Stoeckmann, JY Park, M Turowski, V Hagenmeyer, C Miller Energy and Buildings 265, 112096, 2022 | 6 | 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 |
| 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 | 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 |
| 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 |
| 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 |
| 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 | 1 | 2022 |
| 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: Berlin, 25. - 26 …, 2021 | 1 | 2021 |
| 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 | | 2023 |
| 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 |
| RO-Crate Time Series Exporter for the Building Consumption Data of KIT Campus North J Schweikert, M Turowski, V Köbe, W Süß, V Hagenmeyer 1st Conference on Research Data Infrastructure (CoRDI 2023), Karlsruhe …, 2023 | | 2023 |
| Data-Driven Methods for Managing Anomalies in Energy Time Series M Turowski | | 2023 |
Veit HagenmeyerKITVerified email at kit.edu
