Theme 4: Brain Networks and Neuronal Communication

Machine Learning (Biophysics)

Donders Institute for Brain, Cognition and Behaviour My research focuses on the computational challenge that one faces when trying to understand intelligent behavior in natural systems, or when one attempts to build artificial intelligence.

For instance, intelligent behavior is adaptive and changes on the basis of past seen data; it requires integration of sensory data with prior knowledge; and it must be robust to noise. These problems are fundamental and they occur in many intelligent tasks (cf. vision, motor control, memory, etc.). They are shared by natural and artificial intelligence. My general research goal is to provide theoretical insights, models and approaches that address these issues and is at the interface of machine learning and neuro-science.

Contact
Name:	Bert Kappen
Telephone:	024-3614241
Email:	b.kappen@science.ru.nl
Fax:	024-3541435
Visiting address:	Department of Biophysics Radboud University Nijmegen Heyendaalseweg 135 6525 AJ Nijmegen The Netherlands
Postal address:	Department of Biophysics Radboud University Nijmegen P.O. Box 9010 6500 GL Nijmegen The Netherlands

Projects

BrainGain (Smart mix)

Genetic association study using machine learning methods (Donders internal round)

Brain imaging, genetics and psychiatry using machine learning methods (NWO Cognition)

Multi-agent systems (with Thales D-Cis lab)

Bonaparte (Smart Research with the Dutch Forensic Institute)

Bovinose (Smart Research, EU FP7)

CompLACS (EU FP7)

SUMO (EU FP7)

NETT

Key publications

Kappen H.J., Gómez V., Opper M. Optimal control as a graphical model inference problem Machine Learning, vol. 87, no. 2, pp. 159-182, 2012 pdf

Kappen H.J. The variational garrote Machine Learning, pp. 1-17, 2012

Llera A., Gómez V., Kappen H.J. Adaptive classification on brain computer interfaces using reinforcement signals Neural Computation, vol. 24, no. 11, pp. 2900-2923, 2012

Gheshlaghi Azar M., Munos R., Kappen H.J. On the sample complexity of reinforcement learning with a generative model Proceedings of the International Conference on Machine Learning Learning, vol. 29 th, pp. 1-11, 2012 pdf

Torres J.J., Kappen H.J. Emerging phenomena in neural networks with dynamic synapses and their computational implications pdf

Links

SNN Adaptive Intelligence

Back to:
Theme 4:
Natural Computing & Neurotechnology

Research Group
Machine Learning (Biophysics)

Principal Investigator
Prof.dr. Bert Kappen

Group members
dr. Wim Wiegerinck

Postdocs
dr. Eduardo Dominguez Vázquez

PhD candidates
Onno Huijgen
Peyman Najafi
Aarón Villanueva

Programmer Smart Research bv
dr.ing. Willem Burgers

(Update January 2023)