| A synthetic energy dataset for non-intrusive load monitoring in households C Klemenjak, C Kovatsch, M Herold, W Elmenreich Scientific data 7 (1), 108, 2020 | 121 | 2020 |
| Adaptive weighted recurrence graphs for appliance recognition in non-intrusive load monitoring A Faustine, L Pereira, C Klemenjak IEEE Transactions on Smart Grid 12 (1), 398-406, 2020 | 104 | 2020 |
| Non-intrusive load monitoring: A review and outlook C Klemenjak, P Goldsborough arXiv preprint arXiv:1610.01191, 2016 | 87 | 2016 |
| Towards comparability in non-intrusive load monitoring: On data and performance evaluation C Klemenjak, S Makonin, W Elmenreich 2020 IEEE power & energy society innovative smart grid technologies …, 2020 | 61 | 2020 |
| YoMo: the Arduino-based smart metering board C Klemenjak, D Egarter, W Elmenreich Computer Science-Research and Development 31, 97-103, 2016 | 56 | 2016 |
| Electricity consumption data sets: Pitfalls and opportunities C Klemenjak, A Reinhardt, L Pereira, S Makonin, M Bergés, ... Proceedings of the 6th ACM international conference on systems for energy …, 2019 | 46 | 2019 |
| How does load disaggregation performance depend on data characteristics? insights from a benchmarking study A Reinhardt, C Klemenjak Proceedings of the eleventh ACM international conference on future energy …, 2020 | 38 | 2020 |
| Augmenting an assisted living lab with non-intrusive load monitoring H Bousbiat, C Klemenjak, G Leitner, W Elmenreich 2020 IEEE international instrumentation and measurement technology …, 2020 | 26 | 2020 |
| On metrics to assess the transferability of machine learning models in non-intrusive load monitoring C Klemenjak, A Faustine, S Makonin, W Elmenreich arXiv preprint arXiv:1912.06200, 2019 | 24 | 2019 |
| Exploring time series imaging for load disaggregation H Bousbiat, C Klemenjak, W Elmenreich Proceedings of the 7th ACM International Conference on Systems for Energy …, 2020 | 23 | 2020 |
| YoMoPie: A User-Oriented Energy Monitor to Enhance Energy Efficiency in Households C Klemenjak, S Jost, W Elmenreich 2018 IEEE Conference on Technologies for Sustainability (SusTech), 7, 0 | 17* | |
| Investigating the performance gap between testing on real and denoised aggregates in non-intrusive load monitoring C Klemenjak, S Makonin, W Elmenreich Energy Informatics 4, 1-15, 2021 | 12 | 2021 |
| Unlocking the Full Potential of Neural NILM: On Automation, Hyperparameters, and Modular Pipelines H Bousbiat, A Faustine, C Klemenjak, L Pereira, W Elmenreich IEEE Transactions on Industrial Informatics 19 (5), 7002-7010, 2022 | 9 | 2022 |
| 2020 IEEE power & energy society innovative smart grid technologies conference (ISGT) C Klemenjak, S Makonin, W Elmenreich IEEE, 2020 | 9 | 2020 |
| Device-free user activity detection using non-intrusive load monitoring: a case study A Reinhardt, C Klemenjak Proceedings of the 2nd ACM Workshop on Device-Free Human Sensing, 1-5, 2020 | 8 | 2020 |
| On the Applicability of Correlation Filters for Appliance Detection in Smart Meter Readings C Klemenjak, W Elmenreich 2017 IEEE International Conference on Smart Grid Communications (SmartGridComm), 2018 | 7 | 2018 |
| On metrics to assess the transferability of machine learning models in non-intrusive load monitoring. arXiv 2019 C Klemenjak, A Faustine, S Makonin, W Elmenreich arXiv preprint arXiv:1912.06200, 0 | 7 | |
| Stop: Exploring bayesian surprise to better train nilm R Jones, C Klemenjak, S Makonin, IV Bajić Proceedings of the 5th International Workshop on Non-Intrusive Load …, 2020 | 6 | 2020 |
| Exploring Bayesian surprise to prevent overfitting and to predict model performance in non-intrusive load monitoring R Jones, C Klemenjak, S Makonin, IV Bajic arXiv preprint arXiv:2009.07756, 2020 | 6 | 2020 |
| On metrics to assess the transferability of machine learning models in non-intrusive load monitoring. arXiv C Klemenjak, A Faustine, S Makonin, W Elmenreich arXiv preprint arXiv:1912.06200, 2019 | 5 | 2019 |
Wilfried ElmenreichProfessor of Smart Grids, University of KlagenfurtBestätigte E-Mail-Adresse bei aau.at