| Deep learning for estimating building energy consumption E Mocanu, PH Nguyen, M Gibescu, WL Kling Sustainable Energy, Grids and Networks 6, 91-99, 2016 | 230 | 2016 |
| On-line building energy optimization using deep reinforcement learning E Mocanu, DC Mocanu, PH Nguyen, A Liotta, ME Webber, M Gibescu, ... IEEE transactions on smart grid 10 (4), 3698-3708, 2018 | 119 | 2018 |
| Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science DC Mocanu, E Mocanu, P Stone, PH Nguyen, M Gibescu, A Liotta Nature communications 9 (1), 1-12, 2018 | 86 | 2018 |
| Unsupervised energy prediction in a smart grid context using reinforcement cross-building transfer learning E Mocanu, PH Nguyen, WL Kling, M Gibescu Energy and Buildings 116, 646-655, 2016 | 58 | 2016 |
| A topological insight into restricted boltzmann machines DC Mocanu, E Mocanu, PH Nguyen, M Gibescu, A Liotta Machine Learning 104 (2-3), 243-270, 2016 | 47 | 2016 |
| Comparison of machine learning methods for estimating energy consumption in buildings E Mocanu, PH Nguyen, M Gibescu, WL Kling 2014 international conference on probabilistic methods applied to power …, 2014 | 36 | 2014 |
| Big IoT data mining for real-time energy disaggregation in buildings DC Mocanu, E Mocanu, PH Nguyen, M Gibescu, A Liotta 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2016 | 30 | 2016 |
| Enabling cooperative behavior for building demand response based on extended joint action learning LA Hurtado, E Mocanu, PH Nguyen, M Gibescu, RIG Kamphuis IEEE Transactions on Industrial Informatics 14 (1), 127-136, 2017 | 24 | 2017 |
| Deep learning versus traditional machine learning methods for aggregated energy demand prediction NG Paterakis, E Mocanu, M Gibescu, B Stappers, W van Alst 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT …, 2017 | 23 | 2017 |
| Demand forecasting at low aggregation levels using factored conditional restricted boltzmann machine E Mocanu, PH Nguyen, M Gibescu, EM Larsen, P Pinson 2016 Power Systems Computation Conference (PSCC), 1-7, 2016 | 22 | 2016 |
| Energy disaggregation for real-time building flexibility detection E Mocanu, PH Nguyen, M Gibescu 2016 IEEE Power and Energy Society General Meeting (PESGM), 1-5, 2016 | 20 | 2016 |
| Comfort-constrained demand flexibility management for building aggregations using a decentralized approach LA Hurtado, E Mocanu, PH Nguyen, M Gibescu, WL Kling 2015 International Conference on Smart Cities and Green ICT Systems …, 2015 | 19 | 2015 |
| Inexpensive user tracking using boltzmann machines E Mocanu, DC Mocanu, HB Ammar, Z Zivkovic, A Liotta, E Smirnov 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 1-6, 2014 | 16 | 2014 |
| Optimizing the energy exchange between the smart grid and building systems E Mocanu, KO Aduda, PH Nguyen, G Boxem, W Zeiler, M Gibescu, ... 2014 49th International Universities Power Engineering Conference (UPEC), 1-6, 2014 | 12 | 2014 |
| Machine learning applied to smart grids E Mocanu PhD thesis, Technische Universiteit Eindhoven, 2017 | 9 | 2017 |
| Medium Voltage DC Power Systems on Ships: An Offline Parameter Estimation for Tuning the Controllers’ Linearizing Function D Bosich, G Sulligoi, E Mocanu, M Gibescu IEEE Transactions on Energy Conversion 32 (2), 748-758, 2017 | 8 | 2017 |
| Deep learning for power system data analysis E Mocanu, HP Nguyen, M Gibescu Book chapter in Big data application in power systems, 2017 | 6 | 2017 |
| The potential and possible effects of power grid support activities on buildings: An analysis of experimental results for ventilation system KO Aduda, E Mocanu, G Boxem, PH Nguyen, WL Kling, W Zeiler 2014 49th International Universities Power Engineering Conference (UPEC), 1-6, 2014 | 5 | 2014 |
| Statistical Learning versus Deep Learning: Performance Comparison for Building Energy Prediction Methods PA Mynhoff, E Mocanu, M Gibescu Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 2018 …, 2018 | 4 | 2018 |
| One-shot learning using mixture of variational autoencoders: a generalization learning approach DC Mocanu, E Mocanu International Conference on Autonomous Agents and Multiagent Systems (AAMAS …, 2018 | 4 | 2018 |
Madeleine GibescuProfessor of Intermittent Renewable Energy, Utrecht UniversityVerified email at uu.nl
