School of Informatics AUTh
Mischos, S., Dalagdi, E. & Vrakas, D. Intelligent energy management systems: a review. Artif Intell Rev (2023). https://doi.org/10.1007/s10462-023-10441-3
N. V. Gkalinikis and D. Vrakas, "Efficient Deep Learning Techniques for Water Disaggregation," 2022 2nd International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED), Thessaloniki, Greece, 2022, pp. 1-6, doi: 10.1109/SyNERGYMED55767.2022.9941424.
Virtsionis Gkalinikis, Nikolaos, Christoforos Nalmpantis, and Dimitris Vrakas. 2022. "Torch-NILM: An Effective Deep Learning Toolkit for Non-Intrusive Load Monitoring in Pytorch" Energies 15, no. 7: 2647. https://doi.org/10.3390/en15072647
Nalmpantis, Christoforos, Nikolaos Virtsionis Gkalinikis, and Dimitris Vrakas. 2022. "Neural Fourier Energy Disaggregation" Sensors 22, no. 2: 473. https://doi.org/10.3390/s22020473
Lentzas, A.; Dalagdi, E.; Vrakas, D. Multilabel Classification Methods for Human Activity Recognition: A Comparison of Algorithms. Sensors 2022, 22, 2353.
Lentzas A. , and Vrakas D. (2022). Machine learning approaches for non-intrusive home absence detection based on appliance electrical use. Expert Systems with Applications, 210:118454.
A. Vassiliades, N. Bassiliades, Th. Patkos, D. Vrakas, "An Open-Ended Web Knowledge Retrieval Framework for the Household Domain With Explanation and Learning Through Argumentation", International Journal on Semantic Web and Information Systems, Volume 18, no. 1, Article 21, pp.1-34, 2022.
Virtsionis-Gkalinikis, N., Nalmpantis, C. & Vrakas, D. SAED: self-attentive energy disaggregation. Mach Learn (2021). https://doi.org/10.1007/s10994-021-06106-3
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.