Louis Wehenkel
Louis Wehenkel
Professor of EE&CS, Montefiore Institute, ULiège - University of Liège
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Zitiert von
Zitiert von
Extremely randomized trees
P Geurts, D Ernst, L Wehenkel
Machine learning 63, 3-42, 2006
Inferring regulatory networks from expression data using tree-based methods
VA Huynh-Thu, A Irrthum, L Wehenkel, P Geurts
PLoS One 5 (9), e12776, 2010
Wisdom of crowds for robust gene network inference
D Marbach, JC Costello, R Küffner, NM Vega, RJ Prill, DM Camacho, ...
Nature Methods, 796–804, 2012
Tree-based batch mode reinforcement learning
D Ernst, P Geurts, L Wehenkel
Journal of Machine Learning Research 6, 503-556, 2005
Understanding variable importances in forests of randomized trees
G Louppe, L Wehenkel, A Sutera, P Geurts
Advances in neural information processing systems 26, 2013
A complete fuzzy decision tree technique
C Olaru, L Wehenkel
Fuzzy sets and systems 138 (2), 221-254, 2003
State-of-the-art, challenges, and future trends in security constrained optimal power flow
F Capitanescu, JLM Ramos, P Panciatici, D Kirschen, AM Marcolini, ...
Electric power systems research 81 (8), 1731-1741, 2011
Automatic learning techniques in power systems
LA Wehenkel
Springer Science & Business Media, 1998
Random subwindows for robust image classification
R Marée, P Geurts, J Piater, L Wehenkel
2005 IEEE Computer Society Conference on Computer Vision and Pattern …, 2005
Contingency Ranking With Respect to Overloads in Very Large Power Systems Taking Into Account Uncertainty, Preventive, and Corrective Actions
S Fliscounakis, P Panciatici, F Capitanescu, L Wehenkel
IEEE Transactions on Power Systems 28 (4), 4909-4917, 2013
Power systems stability control: reinforcement learning framework
D Ernst, M Glavic, L Wehenkel
IEEE transactions on power systems 19 (1), 427-435, 2004
Supervised learning with decision tree-based methods in computational and systems biology
P Geurts, A Irrthum, L Wehenkel
Molecular Biosystems 5 (12), 1593-1605, 2009
Reinforcement learning versus model predictive control: a comparison on a power system problem
D Ernst, M Glavic, F Capitanescu, L Wehenkel
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 39 …, 2008
Contingency filtering techniques for preventive security-constrained optimal power flow
F Capitanescu, M Glavic, D Ernst, L Wehenkel
IEEE Transactions on Power Systems 22 (4), 1690-1697, 2007
Interior-point based algorithms for the solution of optimal power flow problems
F Capitanescu, M Glavic, D Ernst, L Wehenkel
Electric Power systems research 77 (5-6), 508-517, 2007
A machine learning-based approximation of strong branching
A Marcos Alvarez, Q Louveaux, L Wehenkel
INFORMS Journal on Computing 29 (1), 185-195, 2017
An artificial intelligence framework for online transient stability assessment of power systems
L Wehenkel, T Van Cutsem, M Ribbens-Pavella
IEEE Transactions on Power Systems 4 (2), 789-800, 1989
SIME: A hybrid approach to fast transient stability assessment and contingency selection
Y Zhang, L Wehenkel, P Rousseaux, M Pavella
International Journal of Electrical Power & Energy Systems 19 (3), 195-208, 1997
Machine learning approaches to power-system security assessment
L Wehenkel
IEEE Expert 12 (5), 60-72, 1997
Recent developments in machine learning for energy systems reliability management
L Duchesne, E Karangelos, L Wehenkel
Proceedings of the IEEE 108 (9), 1656-1676, 2020
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