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Jonas Vlasselaer
Jonas Vlasselaer
AI Expert at DeltaRay
Verified email at deltaray.eu
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Cited by
Year
LS-SVM based spectral clustering and regression for predicting maintenance of industrial machines
R Langone, C Alzate, B De Ketelaere, J Vlasselaer, W Meert, ...
Engineering Applications of Artificial Intelligence 37, 268-278, 2015
1002015
Problog2: Probabilistic logic programming
A Dries, A Kimmig, W Meert, J Renkens, G Van den Broeck, J Vlasselaer, ...
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2015
672015
Anytime inference in probabilistic logic programs with Tp-compilation
J Vlasselaer, G Van den Broeck, A Kimmig, W Meert, L De Raedt
Proceedings of 24th International Joint Conference on Artificial …, 2015
452015
Exploiting local and repeated structure in dynamic Bayesian networks
J Vlasselaer, W Meert, G Van den Broeck, L De Raedt
Artificial Intelligence 232, 43-53, 2016
372016
Tp-compilation for inference in probabilistic logic programs
J Vlasselaer, G Van den Broeck, A Kimmig, W Meert, L De Raedt
International Journal of Approximate Reasoning 78, 15-32, 2016
352016
Compiling probabilistic logic programs into sentential decision diagrams
J Vlasselaer, J Renkens, G Van den Broeck, L De Raedt
Proceedings Workshop on Probabilistic Logic Programming (PLP), 1-10, 2014
192014
The most probable explanation for probabilistic logic programs with annotated disjunctions
D Shterionov, J Renkens, J Vlasselaer, A Kimmig, W Meert, G Janssens
Inductive Logic Programming: 24th International Conference, ILP 2014, Nancy …, 2015
182015
ProbLog2: From probabilistic programming to statistical relational learning
J Renkens, D Shterionov, G Van den Broeck, J Vlasselaer, D Fierens, ...
Proceedings of the NIPS Probabilistic Programming Workshop, 2012
152012
Knowledge compilation and weighted model counting for inference in probabilistic logic programs
J Vlasselaer, A Kimmig, A Dries, W Meert, L De Raedt
Proceedings of the First Workshop on Beyond NP, 359-364, 2016
122016
Efficient probabilistic inference for dynamic relational models
J Vlasselaer, W Meert, G Van den Broeck, L De Raedt
AAAI Workshop-Technical Report, 131-134, 2014
122014
Dynamic sensor-frontend tuning for resource efficient embedded classification
L Galindez, K Badami, J Vlasselaer, W Meert, M Verhelst
IEEE Journal on Emerging and Selected Topics in Circuits and Systems 8 (4 …, 2018
82018
Statistical relational learning for prognostics
J Vlasselaer, W Meert
Proceedings of the 21st Belgian-Dutch Conference on Machine Learning, 45-50, 2012
82012
Towards resource-efficient classifiers for always-on monitoring
J Vlasselaer, W Meert, M Verhelst
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2019
72019
A relaxed tseitin transformation for weighted model counting
W Meert, J Vlasselaer, G Van den Broeck
Proceedings of the Sixth International Workshop on Statistical Relational AI …, 2016
62016
Condition monitoring with incomplete observations
J Vlasselaer, W Meert, R Langone, L De Raedt
ECAI 2014, 1215-1216, 2014
22014
BEHAVE-Behavioral analysis of visual events for assisted living scenarios
C Fernando Crispim-Junior, J Vlasselaer, A Dries, F Bremond
Proceedings of the IEEE International Conference on Computer Vision …, 2017
12017
Feature Noise Tuning for Resource Efficient Bayesian Network Classifiers
LI Galindez Olascoaga, J Vlasselaer, W Meert, M Verhelst
ESANN 2018 proceedings, European Symposium on Artificial Neural Networks …, 2018
2018
Dynamic Sensor-Frontend Tuning f
L Galindez, K Badami, J Vlasselaer, W Meert, M Verhlest
Citation Laura Galindez, Komail Badami, Jonas Vlasselaer, Wannes Meert …, 2018
2018
Feature noise tuning for resource efficient Bayesian Network Classifiers.
LIG Olascoaga, J Vlasselaer, W Meert, M Verhelst
ESANN, 2018
2018
Probabilistic Inference for Dynamic and Relational Models
J Vlasselaer
2016
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