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Cedric De Boom
Cedric De Boom
Data Minded
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Title
Cited by
Cited by
Year
Representation learning for very short texts using weighted word embedding aggregation
C De Boom, S Van Canneyt, T Demeester, B Dhoedt
Pattern Recognition Letters 80, 150-156, 2016
2642016
Learning semantic similarity for very short texts
C De Boom, S Van Canneyt, S Bohez, T Demeester, B Dhoedt
2015 IEEE International Conference on Data Mining Workshop (ICDMW), 1229-1234, 2015
1082015
Learning generative state space models for active inference
O Çatal, S Wauthier, C De Boom, T Verbelen, B Dhoedt
Frontiers in Computational Neuroscience 14, 574372, 2020
462020
Learning perception and planning with deep active inference
O Çatal, T Verbelen, J Nauta, C De Boom, B Dhoedt
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
422020
Active vision for robot manipulators using the free energy principle
T Van de Maele, T Verbelen, O Çatal, C De Boom, B Dhoedt
Frontiers in neurorobotics 15, 642780, 2021
312021
Semantics-driven event clustering in Twitter feeds
C De Boom, S Van Canneyt, B Dhoedt
Making sense of microposts 1395, 2-9, 2015
292015
Large-scale user modeling with recurrent neural networks for music discovery on multiple time scales
C De Boom, R Agrawal, S Hansen, E Kumar, R Yon, CW Chen, ...
Multimedia Tools and Applications 77, 15385-15407, 2018
222018
Anomaly detection for autonomous guided vehicles using bayesian surprise
O Çatal, S Leroux, C De Boom, T Verbelen, B Dhoedt
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020
172020
Quantifying uncertainty of deep neural networks in skin lesion classification
P Van Molle, T Verbelen, C De Boom, B Vankeirsbilck, J De Vylder, ...
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and …, 2019
142019
Rhythm, chord and melody generation for lead sheets using recurrent neural networks
C De Boom, S Van Laere, T Verbelen, B Dhoedt
Machine Learning and Knowledge Discovery in Databases: International …, 2020
132020
Optimizing the popularity of Twitter messages through user categories
R Lemahieu, S Van Canneyt, C De Boom, B Dhoedt
2015 IEEE international conference on data mining workshop (ICDMW), 1396-1401, 2015
132015
Deep active inference for autonomous robot navigation
O Çatal, S Wauthier, T Verbelen, C De Boom, B Dhoedt
Bridging AI and Cognitive Science (BAICS) Workshop 2020, 2020
112020
Learning to grasp from a single demonstration
P Van Molle, T Verbelen, E De Coninck, C De Boom, P Simoens, ...
IAS-15: The 15th International Conference on Intelligent Autonomous Systems, 2018
112018
Sigmoidal NMFD: convolutional NMF with saturating activations for drum mixture decomposition
L Vande Veire, C De Boom, T De Bie
Electronics 10 (3), 284, 2021
102021
Sleep: Model reduction in deep active inference
ST Wauthier, O Çatal, C De Boom, T Verbelen, B Dhoedt
Active Inference: First International Workshop, IWAI 2020, Co-located with …, 2020
102020
Character-level recurrent neural networks in practice: comparing training and sampling schemes
C De Boom, T Demeester, B Dhoedt
Neural Computing and Applications 31, 4001-4017, 2019
102019
Low-latency delivery of news-based video content
J van der Hooft, D Pauwels, C De Boom, S Petrangeli, T Wauters, ...
Proceedings of the 9th ACM Multimedia Systems Conference, 537-540, 2018
82018
Performance characterization of low-latency adaptive streaming from video portals
J van der Hooft, C De Boom, S Petrangeli, T Wauters, F De Turck
IEEE Access 6, 43039-43055, 2018
72018
An HTTP/2 push-based framework for low-latency adaptive streaming through user profiling
J van der Hooft, C De Boom, S Petrangeli, T Wauters, F De Turck
NOMS 2018-2018 IEEE/IFIP Network Operations and Management Symposium, 1-5, 2018
72018
Lazy evaluation of convolutional filters
S Leroux, S Bohez, C De Boom, E De Coninck, T Verbelen, ...
International Conference on Machine Learning: Workshop on Device Intelligence, 2016
72016
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