School of Informatics AUTh
Gkalinikis, N. V., Nalmpantis, C., & Vrakas, D. (2021). SAED: Self-Attentive Energy Disaggregation. In Machine Learning.
C. Nalmpantis, L. Vrysis, D. Vlachava, L. Papageorgiou, D. Vrakas (2021). "Entropy Based Feature Pooling in Speech Command Classification". In Intelligent Computing-Proceedings of the Computing Conference
Gkalinikis, N. V., Nalmpantis, C., & Vrakas, D. (2020, October). Attention in Recurrent Neural Networks for Energy Disaggregation. In International Conference on Discovery Science (pp. 551-565). Springer, Cham.
A. Lentzas and D. Vrakas, "LadyBug. An Intensity based Localization Bug Algorithm," 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Vienna, Austria, 2020, pp. 682-689.
C. Nalmpantis, D. Vrakas, On time series representations for multi-label NILM, Neural Computing and Applications, DOI: 10.1007/s00521-020-04916-5, 2020
A. Lentzas, D. Vrakas, Non-intrusive human activity recognition and abnormal behavior detection on elderly people: a review. Artif Intell Rev 53, 1975–2021, 2020
Nalmpantis C., Vrakas D. (2019) Signal2Vec: Time Series Embedding Representation. In: Macintyre J., Iliadis L., Maglogiannis I., Jayne C. (eds) Engineering Applications of Neural Networks. EANN 2019. Communications in Computer and Information Science, vol 1000. Springer, Cham
Kyrkou L., Nalmpantis C., Vrakas D. (2019) Imaging Time-Series for NILM. In: Macintyre J., Iliadis L., Maglogiannis I., Jayne C. (eds) Engineering Applications of Neural Networks. EANN 2019. Communications in Computer and Information Science, vol 1000. Springer, Cham
Symeonidis N., Nalmpantis C., Vrakas D. (2019) A Benchmark Framework to Evaluate Energy Disaggregation Solutions. In: Macintyre J., Iliadis L., Maglogiannis I., Jayne C. (eds) Engineering Applications of Neural Networks. EANN 2019. Communications in Computer and Information Science, vol 1000. Springer, Cham
C. Nalmpantis, A. Lentzas and D. Vrakas, "A Theoretical Analysis of Pooling Operation Using Information Theory," 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), Portland, OR, USA, 2019, pp. 1729-1733
