Tom Heskes
Tom Heskes
Professor of Computer Science and Artificial Intelligence, Radboud University Nijmegen
Verified email at - Homepage
TitleCited byYear
Task clustering and gating for bayesian multitask learning
B Bakker, T Heskes
Journal of Machine Learning Research 4 (May), 83-99, 2003
MAGMA: generalized gene-set analysis of GWAS data
CA de Leeuw, JM Mooij, T Heskes, D Posthuma
PLoS computational biology 11 (4), e1004219, 2015
Practical confidence and prediction intervals
T Heskes
Advances in neural information processing systems, 176-182, 1997
Energy functions for self-organizing maps
T Heskes
Kohonen maps, 303-315, 1999
Self-organizing maps, vector quantization, and mixture modeling
T Heskes
IEEE transactions on neural networks 12 (6), 1299-1305, 2001
Stable fixed points of loopy belief propagation are local minima of the bethe free energy
T Heskes
Advances in neural information processing systems, 359-366, 2003
On the uniqueness of loopy belief propagation fixed points
T Heskes
Neural Computation 16 (11), 2379-2413, 2004
Learning processes in neural networks
TM Heskes, B Kappen
Physical Review A 44 (4), 2718, 1991
Expectation propagation for approximate inference in dynamic Bayesian networks
T Heskes, O Zoeter
Proceedings of the Eighteenth conference on Uncertainty in artificial …, 2002
Clustering ensembles of neural network models
B Bakker, T Heskes
Neural networks 16 (2), 261-269, 2003
Approximate inference and constrained optimization
T Heskes, K Albers, B Kappen
Proceedings of the Nineteenth conference on Uncertainty in Artificial …, 2002
The statistical properties of gene-set analysis
CA De Leeuw, BM Neale, T Heskes, D Posthuma
Nature Reviews Genetics 17 (6), 353, 2016
On-line learning processes in artificial neural networks
TM Heskes, B Kappen
North-Holland Mathematical Library 51, 199-233, 1993
Convexity arguments for efficient minimization of the Bethe and Kikuchi free energies
T Heskes
Journal of Artificial Intelligence Research 26, 153-190, 2006
Empirical Bayes for learning to learn
TM Heskes
San Francisco: Morgan Kaufmann, 2000
Fractional belief propagation
W Wiegerinck, T Heskes
Advances in Neural Information Processing Systems 15, 438-445, 2003
Premise selection for mathematics by corpus analysis and kernel methods
J Alama, T Heskes, D Kühlwein, E Tsivtsivadze, J Urban
Journal of Automated Reasoning 52 (2), 191-213, 2014
Selecting weighting factors in logarithmic opinion pools
T Heskes
Advances in neural information processing systems, 266-272, 1998
Task-dependent learning of attention
P Van De Laar, T Heskes, S Gielen
Neural networks 10 (6), 981-992, 1997
Efficient Bayesian multivariate fMRI analysis using a sparsifying spatio-temporal prior
MAJ Van Gerven, B Cseke, FP De Lange, T Heskes
NeuroImage 50 (1), 150-161, 2010
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