Machine learning approaches for non-intrusive load monitoring: from qualitative to quantitative comparation C Nalmpantis, D Vrakas Artificial Intelligence Review 52 (1), 217-243, 2019 | 101 | 2019 |
Sliding window approach for online energy disaggregation using artificial neural networks O Krystalakos, C Nalmpantis, D Vrakas Proceedings of the 10th Hellenic Conference on Artificial Intelligence, 1-6, 2018 | 74 | 2018 |
Signal2vec: Time series embedding representation C Nalmpantis, D Vrakas International conference on engineering applications of neural networks, 80-90, 2019 | 19 | 2019 |
On time series representations for multi-label NILM C Nalmpantis, D Vrakas Neural Computing and Applications 32 (23), 17275-17290, 2020 | 18 | 2020 |
Imaging time-series for NILM L Kyrkou, C Nalmpantis, D Vrakas International Conference on Engineering Applications of Neural Networks, 188-196, 2019 | 13 | 2019 |
A benchmark framework to evaluate energy disaggregation solutions N Symeonidis, C Nalmpantis, D Vrakas International Conference on Engineering Applications of Neural Networks, 19-30, 2019 | 8 | 2019 |
Attention in recurrent neural networks for energy disaggregation N Virtsionis Gkalinikis, C Nalmpantis, D Vrakas International Conference on Discovery Science, 551-565, 2020 | 7 | 2020 |
Hyperparameter tuning using quantum genetic algorithms A Lentzas, C Nalmpantis, D Vrakas 2019 IEEE 31st International Conference on Tools with Artificial …, 2019 | 4 | 2019 |
Neural Fourier energy disaggregation C Nalmpantis, N Virtsionis Gkalinikis, D Vrakas Sensors 22 (2), 473, 2022 | 3 | 2022 |
SAED: Self-attentive energy disaggregation N Virtsionis-Gkalinikis, C Nalmpantis, D Vrakas Machine Learning, 1-20, 2021 | 2 | 2021 |
A theoretical analysis of pooling operation using information theory C Nalmpantis, A Lentzas, D Vrakas 2019 IEEE 31st International Conference on Tools with Artificial …, 2019 | 2 | 2019 |
Energy profile representation in vector space C Nalmpantis, O Krystalakos, D Vrakas Proceedings of the 10th Hellenic Conference on Artificial Intelligence, 1-5, 2018 | 1 | 2018 |
Noise invariant feature pooling for the internet of audio things C Nalmpantis, L Vrysis, D Vlachava, L Papageorgiou, D Vrakas Multimedia Tools and Applications, 1-16, 2022 | | 2022 |
Torch-NILM: An Effective Deep Learning Toolkit for Non-Intrusive Load Monitoring in Pytorch N Virtsionis Gkalinikis, C Nalmpantis, D Vrakas Energies 15 (7), 2647, 2022 | | 2022 |
Entropy Based Feature Pooling in Speech Command Classification C Nalmpantis, L Vrysis, D Vlachava, L Papageorgiou, D Vrakas Intelligent Computing, 1083-1091, 2021 | | 2021 |
Data Expedition into the Swiss Twitter Corpus—Workshop Results at SwissText 2018 R Grubenmann, W Fallouh, C Nalmpantis, M Cieliebak | | |