Kappen H.J.
Learning quantum models from quantum or classical data.
Journal of Physics A: Mathematical and Theoretical as a Fast Track Communication,
vol. 53,
pp. 214001,
2020
Kolmus A., Khajetoorians A.A., Kappen H.J.
Atom-by-atom construction of attractors in a tunable finite size spin array.
New Journal of Physics,
vol. 22,
pp. 023038,
2020
Kiraly B, Knol EJ, Kappen H.J., Khajetoorians A.A.
An atomic boltzmann machine capable of on-chip learning.
arxiv,
2020
Thalmeier D., Kappen H.J., Totaro S, Gómez V.
Adaptive smoothing path integral control.
arxiv,
pp. arXiv:2005.06364,
2020
Bergen GLL van, Duenk P, Albers C.A., Bijma P, Calus MPL, Wientjes YJC, Kappen H.J.
Bayesian neural networks with variable selection for prediction of genotypic values.
Genetics,
vol. 52,
pp. 1-14,
2020
Wiersema RC, Kappen H.J.
Implementing perceptron models with qubits.
Physical Review A,
vol. 100,
pp. 020301-6,
2019
McGuire, K.N., Wagter C de, Tuyls K., Kappen H.J., Croon G. de
Minimal navigation solution for a swarm of tiny flying robots to explore an unknown environment.
Science Robotics,
vol. 4,
pp. eaaw9710,
2019
Kappen H.J.
Advanced machine learning.
Course paper,
pp. 1-4,
2019
Duane G.S., Wiegerinck W.A.J.J., Selten F., Shen M.L, Keenlyside N.
Supermodeling: synchronization of alternative dynamical models of a single objective process
.
Advanced in Nonlinear Geosciences,
pp. 101-121,
2018
Duane G.S., Wiegerinck W.A.J.J., Selten F., Shen M.L, Keenlyside N.
Supermodeling: synchronization of alternative dynamical models of a single objective process.
Advanced in Nonlinear Geosciences,
pp. 101-121,
2017
Llera A., Gómez V., Kappen H.J.
Quantitative analysis of task selection for brain–computer interfaces..
Journal of Neural Engineering,
vol. 11,
no. 5,
pp. 056002,
2014
Llera A., Gómez V., Kappen H.J.
Is task selection a solution for bci
illiteracy?.
Journal of Neural Engeneering,
2013
Berge L.A., Selten F.M., Wiegerinck W.A.J.J., Duane G.S.
A multi-model ensemble method that combines imperfect models through learning.
Earth System Dynamics,
vol. 2,
pp. 161-177,
2011
Wiegerinck W.A.J.J., Setkus A., Buda V., Borg-Karlson A.-K, Mozuraitis R.
Bovinose: pheromone-based sensor system for detecting estrus in dairy cows.
The European Future Technologies Conference and Exhibition,
vol. FET 11,
pp. 340-342,
2011
Heskes T.M.
The use of being stubborn and introspective.
Prerational Intelligence: Adaptive Behavior and Intelligent Systems Without Symbols and Logic.,
vol. 2,
pp. 725-741,
2000
Heskes T.M.
Empirical bayes for learning to learn.
Int. Conference on Machine Learning,
pp. 367-374,
2000
Bakker B.
A neural-bayesian approach to survival analysis.
Proceedings International Conference on Artificial Neural Networks 9,
vol. 2,
pp. 832-837,
1999
Barber D., Bishop C.M.
Ensemble learning in bayesian neural networks.
Neural Networks and Machine learning,
vol. 168,
pp. 215-238,
1998
Nijman M.J., Kappen H.J.
Symmetry breaking and training from incomplete data with radial basis boltzmann machines.
International Journal of Neural Systems A,
vol. 8,
pp. 301-316,
1997
Kappen H.J.
Classification with inquiry.
UNKNOWN,
1996
Nijman M.J., Kappen H.J.
Radial basis boltzmann machines and incomplete data.
UNKNOWN,
1995
Kappen H.J., Nijman M.J., Moorsel T. van
Learning active vision: industrial application processing systems,.
Artificial Neural Networks 5, Session 7, Robotics,
pp. 193-202,
1995