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Dirk Gorissen
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2020 – today
- 2021
- [j7]Hazel Wilkinson, James Briggs, Dirk Gorissen:
Computer Vision and the Creation of a Database of Printers' Ornaments. Digit. Humanit. Q. 15(1) (2021)
2010 – 2019
- 2013
- [c16]Ivo Couckuyt, Dirk Gorissen, Karel Crombecq, Dirk Deschrijver
, Tom Dhaene:
The SUMO toolbox: A tool for automatic regression modeling and active learning. AFRICON 2013: 1-4 - 2012
- [j6]Ivo Couckuyt, A. Forrester, Dirk Gorissen, Filip De Turck
Blind Kriging: Implementation and performance analysis. Adv. Eng. Softw. 49: 1-13 (2012) - 2011
- [j5]Karel Crombecq, Dirk Gorissen, Dirk Deschrijver
A Novel Hybrid Sequential Design Strategy for Global Surrogate Modeling of Computer Experiments. SIAM J. Sci. Comput. 33(4): 1948-1974 (2011) - [c15]Huu Minh Nguyen, Ivo Couckuyt, Luc Knockaert, Tom Dhaene, Dirk Gorissen, Yvan Saeys
An alternative approach to avoid overfitting for surrogate models. WSC 2011: 2765-2776 - [c14]Ivo Couckuyt, Filip De Turck, Tom Dhaene, Dirk Gorissen:
Automatic surrogate model type selection during the optimization of expensive black-box problems. WSC 2011: 4274-4284 - 2010
- [j4]Dirk Gorissen, Ivo Couckuyt, Eric Laermans, Tom Dhaene:
Multiobjective global surrogate modeling, dealing with the 5-percent problem. Eng. Comput. 26(1): 81-98 (2010) - [j3]Dirk Gorissen, Ivo Couckuyt, Piet Demeester, Tom Dhaene, Karel Crombecq:
A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design. J. Mach. Learn. Res. 11: 2051-2055 (2010)
2000 – 2009
- 2009
- [j2]Dirk Gorissen, Tom Dhaene, Filip De Turck:
Evolutionary Model Type Selection for Global Surrogate Modeling. J. Mach. Learn. Res. 10: 2039-2078 (2009) - [j1]Dirk Gorissen, Luciano De Tommasi
Sequential modeling of a low noise amplifier with neural networks and active learning. Neural Comput. Appl. 18(5): 485-494 (2009) - [c13]Dirk Gorissen:
Grid-Enabled Adaptive Metamodeling and Active Learning for Computer Based Design. Canadian AI 2009: 266-269 - [c12]Dirk Gorissen, Ivo Couckuyt, Eric Laermans, Tom Dhaene:
Pareto-Based Multi-output Metamodeling with Active Learning. EANN 2009: 389-400 - [c11]Dirk Gorissen, Ivo Couckuyt, Karel Crombecq, Tom Dhaene:
Pareto-Based Multi-output Model Type Selection. HAIS 2009: 442-449 - [c10]Ivo Couckuyt, Dirk Gorissen, Hamed Rouhani, Eric Laermans, Tom Dhaene:
Evolutionary Regression Modeling with Active Learning: An Application to Rainfall Runoff Modeling. ICANNGA 2009: 548-558 - [c9]Karel Crombecq, Dirk Gorissen, Luciano De Tommasi
A Novel Sequential Design Strategy for Global Surrogate Modeling. WSC 2009: 731-742 - [p1]Dirk Gorissen, Karel Crombecq, Ivo Couckuyt, Tom Dhaene:
Automatic Approximation of Expensive Functions with Active Learning. Foundations of Computational Intelligence (1) 2009: 35-62 - 2008
- [c8]Dirk Gorissen, Luciano De Tommasi
Automatic model type selection with heterogeneous evolution: An application to RF circuit block modeling. IEEE Congress on Evolutionary Computation 2008: 989-996 - [c7]Karel Crombecq, Luciano De Tommasi, Dirk Gorissen, Tom Dhaene:
A comparison of sequential design methods for RF circuit block modeling. WSC 2008: 2942 - 2007
- [c6]Dirk Gorissen, Wouter Hendrickx, Tom Dhaene:
Adaptive Global Metamodeling with Neural Networks. ESANN 2007: 187-192 - 2006
- [c5]Dirk Gorissen, Wouter Hendrickx, Karel Crombecq, Tom Dhaene:
Integrating Gridcomputing and Metamodeling. CCGRID 2006: 185-192 - [c4]Dirk Gorissen, Piotr Wendykier, Dawid Kurzyniec, Vaidy S. Sunderam:
Integrating heterogeneous information services using JNDI. IPDPS 2006 - [c3]Dirk Gorissen, Karel Crombecq, Wouter Hendrickx, Tom Dhaene:
Adaptive Distributed Metamodeling. VECPAR 2006: 579-588 - [c2]Wouter Hendrickx, Dirk Gorissen, Tom Dhaene:
Grid enabled sequential design and adaptive metamodeling. WSC 2006: 872-881 - 2005
- [c1]Dirk Gorissen, Gunther Stuer, Kurt Vanmechelen, Jan Broeckhove:
H2O Metacomputing - Jini Lookup and Discovery. International Conference on Computational Science (2) 2005: 1072-1079
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