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Wim Wiegerinck
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- affiliation: Radboud University Nijmegen, Netherlands
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2010 – 2019
- 2016
- [i5]Bert Kappen, Wim Wiegerinck:
Bonaparte: Bayesian Networks to Give Victims back their Names. ERCIM News 2016(107) (2016) - 2013
- [p2]Wim Wiegerinck, Willem Burgers, Bert Kappen:
Bayesian Networks, Introduction and Practical Applications. Handbook on Neural Information Processing 2013: 401-431 - [i4]Wim Wiegerinck, Tom Heskes:
IPF for Discrete Chain Factor Graphs. CoRR abs/1301.0613 (2013) - [i3]Wim Wiegerinck:
Variational Approximations between Mean Field Theory and the Junction Tree Algorithm. CoRR abs/1301.3901 (2013) - 2012
- [i2]Bart van den Broek, Wim Wiegerinck, Hilbert J. Kappen:
Risk Sensitive Path Integral Control. CoRR abs/1203.3523 (2012) - [i1]Wim Wiegerinck, Bart van den Broek, Hilbert J. Kappen:
Stochastic Optimal Control in Continuous Space-Time Multi-Agent Systems. CoRR abs/1206.6866 (2012) - 2011
- [j13]Bart van den Broek, Wim Wiegerinck, Bert Kappen:
Stochastic optimal control of state constrained systems. Int. J. Control 84(3): 597-615 (2011) - [c19]F. M. Selten, G. S. Duane, Wim Wiegerinck, Noel Keenlyside
, Jürgen Kurths, Ljupco Kocarev:
Supermodeling by Combining Imperfect Models. FET 2011: 261-263 - [c18]W. A. J. J. Wiegerinck, Arunas Setkus
BOVINOSE: Pheromone-Based Sensor System for Detecting Estrus in Dairy Cows. FET 2011: 340-342 - 2010
- [j12]Willem Burgers, Wim Wiegerinck, Bert Kappen, Mirano Spalburg:
A Bayesian petrophysical decision support system for estimation of reservoir compositions. Expert Syst. Appl. 37(12): 7526-7532 (2010) - [c17]Bart van den Broek, Wim Wiegerinck, Hilbert J. Kappen:
Risk Sensitive Path Integral Control. UAI 2010: 615-622 - [p1]Wim Wiegerinck, Bert Kappen, Willem Burgers:
Bayesian Networks for Expert Systems: Theory and Practical Applications. Interactive Collaborative Information Systems 2010: 547-578
2000 – 2009
- 2008
- [j11]Bart van den Broek, Wim Wiegerinck, Bert Kappen:
Graphical Model Inference in Optimal Control of Stochastic Multi-Agent Systems. J. Artif. Intell. Res. 32: 95-122 (2008) - 2007
- [c16]Bart van den Broek, Wim Wiegerinck, Bert Kappen:
Optimal Control in Large Stochastic Multi-agent Systems. Adaptive Agents and Multi-Agents Systems 2007: 15-26 - [c15]Bastian Wemmenhove, Joris M. Mooij, Wim Wiegerinck, Martijn A. R. Leisink, Hilbert J. Kappen, Jan P. Neijt:
Inference in the Promedas Medical Expert System. AIME 2007: 456-460 - [c14]Wim Wiegerinck, Bart van den Broek, Bert Kappen:
Optimal on-line scheduling in stochastic multiagent systems in continuous space-time. AAMAS 2007: 112 - 2006
- [c13]Wim Wiegerinck, Bart van den Broek, Bert Kappen:
Stochastic Optimal Control in Continuous Space-Time Multi-Agent Systems. UAI 2006 - 2005
- [c12]Wim Wiegerinck:
Approximations with Reweighted Generalized Belief Propagation. AISTATS 2005: 421-428 - [c11]Wim Wiegerinck:
Modeling Bayesian Networks by Learning from Experts. BNAIC 2005: 305-312 - 2004
- [j10]Machiel Westerdijk, Wim Wiegerinck:
Improving classification with latent variable models by sequential constraint optimization. Neurocomputing 56: 167-185 (2004) - 2003
- [j9]Wim Wiegerinck:
Clinical Applications of Artificial Neural Networks: Richard Dybowski, Vanya Gant (Eds.), Cambridge University Press, Cambridge, UK, New York, Oakleigh, Madrid, Cape Town, 2001, 378 pp., 55 figures, 25 tables, Hardcover, ISBN 0521662710. Artif. Intell. Medicine 27(2): 223-226 (2003) - [j8]Tom Heskes
Optimising newspaper sales using neural-Bayesian technology. Neural Comput. Appl. 12(3-4): 212-219 (2003) - [c10]Tom Heskes, Onno Zoeter, Wim Wiegerinck:
Approximate Expectation Maximization. NIPS 2003: 353-360 - 2002
- [c9]Wim Wiegerinck, Tom Heskes:
Fractional Belief Propagation. NIPS 2002: 438-445 - [c8]Wim Wiegerinck, Tom Heskes:
IPF for Discrete Chain Factor Graphs. UAI 2002: 560-567 - 2001
- [j7]Machiel Westerdijk, David Barber, Wim Wiegerinck:
Deterministic Generative Models for Fast Feature Discovery. Data Min. Knowl. Discov. 5(4): 337-363 (2001) - [c7]Hilbert J. Kappen, Wim Wiegerinck:
Novel iteration schemes for the Cluster Variation Method. NIPS 2001: 415-422 - 2000
- [j6]Wim Wiegerinck:
Functional Networks with Applications. A Neural-Based Paradigm, by E. Castillo, A. Cobo, J. M. Gutiérrez and R. E. Pruneda, Kluwer, 1998, ISBN 0-7923-8332-X. Artif. Intell. Medicine 18(3): 267-270 (2000) - [j5]Wim Wiegerinck, Bert Kappen:
Approximations of Bayesian Networks through KL Minimisation. New Gener. Comput. 18(2): 167-176 (2000) - [c6]Machiel Westerdijk, Wim Wiegerinck:
Classification with Multiple Latent Variable Models using Maximum Entropy Discrimination. ICML 2000: 1143-1150 - [c5]Tom Heskes, Jan-Joost Spanjers, Wim Wiegerinck:
EM Algorithms for Self-Organizing Maps. IJCNN (6) 2000: 9-14 - [c4]Hilbert J. Kappen, Wim Wiegerinck:
Second Order Approximations for Probability Models. NIPS 2000: 238-244 - [c3]Wim Wiegerinck:
Variational Approximations between Mean Field Theory and the Junction Tree Algorithm. UAI 2000: 626-633
1990 – 1999
- 1999
- [j4]Wim Wiegerinck, Hilbert J. Kappen, E. W. M. T. ter Braak, W. J. P. P. ter Burg, Marcel J. Nijman, Y. L. O, Jan P. Neijt:
Approximate inference for medical diagnosis. Pattern Recognit. Lett. 20(11-13): 1231-1239 (1999) - [c2]O. Ying-Lie, W. J. P. P. ter Burg, E. W. M. T. ter Braak, Jan P. Neijt, W. A. J. J. Wiegerinck, Marcel J. Nijman, Hilbert J. Kappen:
A Development Protocol for a Diagnostic DSS. MIE 1999: 755-758 - 1998
- [j3]Karin P. Krommenhoek, W. A. J. J. Wiegerinck:
A neural network study of precollicular saccadic averaging. Biol. Cybern. 78(6): 465-477 (1998) - [c1]David Barber, Wim Wiegerinck:
Tractable Variational Structures for Approximating Graphical Models. NIPS 1998: 183-189 - 1996
- [j2]Wim Wiegerinck, Tom Heskes
How Dependencies between Successive Examples Affect On-Line Learning. Neural Comput. 8(8): 1743-1765 (1996) - [j1]Tom Heskes
A theoretical comparison of batch-mode, on-line, cyclic, and almost-cyclic learning. IEEE Trans. Neural Networks 7(4): 919-925 (1996)
Coauthor Index
aka: Bert Kappen
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