Louis Wehenkel
Louis Wehenkel
Professor of Electrical Engineering and Computer Science, University of Liège
Verified email at ulg.ac.be - Homepage
Cited by
Cited by
Extremely randomized trees
P Geurts, D Ernst, L Wehenkel
Machine learning 63 (1), 3-42, 2006
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
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
Understanding variable importances in forests of randomized trees
G Louppe, L Wehenkel, A Sutera, P Geurts
Advances in neural information processing systems 26, 431-439, 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, 1-9, 2013
Power systems stability control: reinforcement learning framework
D Ernst, M Glavic, L Wehenkel
IEEE transactions on power systems 19 (1), 427-435, 2004
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
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
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
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
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
Decision tree based transient stability method a case study
L Wehenkel, M Pavella, E Euxibie, B Heilbronn
IEEE Transactions on Power Systems 9 (1), 459-469, 1994
Proteomic mass spectra classification using decision tree based ensemble methods
P Geurts, M Fillet, D De Seny, MA Meuwis, M Malaise, MP Merville, ...
Bioinformatics 21 (14), 3138-3145, 2005
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