Appliance classification using VI trajectories and convolutional neural networks L De Baets, J Ruyssinck, C Develder, T Dhaene, D Deschrijver Energy and Buildings 158, 32-36, 2018 | 248 | 2018 |
Detection of unidentified appliances in non-intrusive load monitoring using siamese neural networks L De Baets, C Develder, T Dhaene, D Deschrijver International Journal of Electrical Power & Energy Systems 104, 645-653, 2019 | 125 | 2019 |
A voltage and current measurement dataset for plug load appliance identification in households R Medico, L De Baets, J Gao, S Giri, E Kara, T Dhaene, C Develder, ... Scientific data 7 (1), 49, 2020 | 101 | 2020 |
On the Bayesian optimization and robustness of event detection methods in NILM L De Baets, J Ruyssinck, C Develder, T Dhaene, D Deschrijver Energy and Buildings 145, 57-66, 2017 | 90 | 2017 |
Accurate prediction of blood culture outcome in the intensive care unit using long short-term memory neural networks T Van Steenkiste, J Ruyssinck, L De Baets, J Decruyenaere, F De Turck, ... Artificial intelligence in medicine 97, 38-43, 2019 | 66 | 2019 |
VI-based appliance classification using aggregated power consumption data L De Baets, T Dhaene, D Deschrijver, C Develder, M Berges 2018 IEEE international conference on smart computing (SMARTCOMP), 179-186, 2018 | 46 | 2018 |
Handling imbalance in an extended PLAID L De Baets, C Develder, T Dhaene, D Deschrijver, J Gao, M Berges 2017 Sustainable Internet and ICT for Sustainability (SustainIT), 1-5, 2017 | 43 | 2017 |
Event detection in NILM using cepstrum smoothing L De Baets, J Ruyssinck, D Deschrijver, T Dhaene 3rd International Workshop on Non-Intrusive Load Monitoring, 1-4, 2016 | 37 | 2016 |
Automated classification of appliances using elliptical fourier descriptors L De Baets, C Develder, T Dhaene, D Deschrijver 2017 IEEE International Conference on Smart Grid Communications …, 2017 | 31 | 2017 |
Positive blood culture detection in time series data using a BiLSTM network L De Baets, J Ruyssinck, T Peiffer, J Decruyenaere, F De Turck, ... arXiv preprint arXiv:1612.00962, 2016 | 11 | 2016 |
Optimized statistical test for event detection in non-intrusive load monitoring L De Baets, J Ruyssinck, C Develder, T Dhaene, D Deschrijver 2017 IEEE International Conference on Environment and Electrical Engineering …, 2017 | 8 | 2017 |
Energy flexibility assessment of an industrial coldstore process J van der Herten, F Depuydt, L De Baets, D Deschrijver, M Strobbe, ... 2016 IEEE International Energy Conference (ENERGYCON), 1-6, 2016 | 8 | 2016 |
Identifying novel neuroblastoma oncogenes using machine learning L De Baets | 4 | 2014 |
Unsupervised trajectory inference using graph mining L De Baets, S Van Gassen, T Dhaene, Y Saeys Computational Intelligence Methods for Bioinformatics and Biostatistics …, 2016 | 3 | 2016 |
Machinaal leren voor het niet-invasief opmeten van stroomverbruik in een woning-Machine Learning for Non-Intrusive Load Monitoring L De Baets | 1 | 2018 |
Machine learning for non-intrusive load monitoring L De Baets Ghent University, 2018 | 1 | 2018 |
Optimized statistical test for event detection in NILM L De Baets, J Ruyssinck, C Develder, T Dhaene, D Deschrijver | | 2017 |
Cepstrum analysis applied on event detection in NILM L De Baets, J Ruyssinck, D Deschrijver, T Dhaene 25th Belgian-Dutch Conference on Machine Learning (Benelearn), 2016 | | 2016 |
Computational inference of developmental chronology using flow cytometry data L De Baets, T Dhaene, Y Saeys 30th Congress of the International Society for Advancement of Cytometry, 165-165, 2015 | | 2015 |
Identifying novel neuroblastoma oncogenes using semi-supervised learning L De Baets, R Cannoodt, J Ruyssinck, K De Preter, T Dhaene, Y Saeys 9th Benelux Bioinformatics conference (BBC-2014), 2014 | | 2014 |