Leen De Baets
Title
Cited by
Cited by
Year
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
482018
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
372017
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
182019
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
182016
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
102019
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
82018
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
82017
Identifying novel neuroblastoma oncogenes using machine learning
L De Baets
42014
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
32017
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
32016
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
32016
Unsupervised trajectory inference using graph mining
L De Baets, S Van Gassen, T Dhaene, Y Saeys
International Meeting on Computational Intelligence Methods for …, 2015
22015
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
12017
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), 1-10, 2020
2020
Machine learning for non-intrusive load monitoring
L De Baets
Ghent University, 2018
2018
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), 1-3, 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
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