| Feature-based Comparison and Generation of Time Series L Kegel, M Hahmann, W Lehner Proceedings of the 30th International Conference on Scientific and …, 2018 | 42 | 2018 |
| Generating What-If Scenarios for Time Series Data L Kegel, M Hahmann, W Lehner Proceedings of the 29th International Conference on Scientific and …, 2017 | 17 | 2017 |
| Template-based Time Series Generation with Loom. L Kegel, M Hahmann, W Lehner EDBT/ICDT Workshops 1558, 2016 | 12 | 2016 |
| ECAST: A Benchmark Framework for Renewable Energy Forecasting Systems. R Ulbricht, U Fischer, L Kegel, D Habich, H Donker, W Lehner EDBT/ICDT Workshops, 148-155, 2014 | 7 | 2014 |
| Feature-driven Time Series Generation L Kegel, M Hahmann, W Lehner 29th GI-Workshop on Foundations of Databases, 2017 | 5 | 2017 |
| Season-and Trend-aware Symbolic Approximation for Accurate and Efficient Time Series Matching L Kegel, C Hartmann, M Thiele, W Lehner Datenbank-Spektrum, 1-12, 2021 | 4 | 2021 |
| Feature-based Time Series Analytics L Kegel Technische Universität Dresden, Dresden, Germany, 2020 | 3 | 2020 |
| Large-Scale Time Series Analytics M Hahmann, C Hartmann, L Kegel, W Lehner Datenbank-Spektrum 19 (1), 17-29, 2019 | 3 | 2019 |
| Feature-aware forecasting of large-scale time series data sets C Hartmann, L Kegel, W Lehner it-Information Technology, 2020 | 1 | 2020 |
| Big by blocks: modular analytics M Hahmann, C Hartmann, L Kegel, D Habich, W Lehner it-Information Technology 58 (4), 176-185, 2016 | 1 | 2016 |
| Accurate and Efficient Time Series Matching by Season-and Trend-aware Symbolic Approximation--Extended Version Including Additional Evaluation and Proofs L Kegel, C Hartmann, M Thiele, W Lehner arXiv preprint arXiv:2105.14867, 2021 | | 2021 |
| Lastgesteuerte Wartung für Prognoseanfragen L Kegel Technische Universität Dresden, 2015 | | 2015 |
