At SNN particular topics are approximate methods for probabilistic ′Bayesian′ inference, control theory, computational neuroscience and data analysis.


SNN: Seminar

Fri, 18-Aug-2017 11:30-13:00

All upcoming SNN events


Bonaparte DNA matching software in a nutshell

Video of Bonaparte.

Recent Articles

An iterative method for nonlinear stochastic optimal control based on path integrals

Satoh Satoshi, Kappen H.J., Saeki M., 2017

Linear {PDEs} and eigenvalue problems corresponding to ergodic stochastic optimization problems on compact manifolds

Bierkens J., Chernyak V.Y., Chertkov M., Kappen H.J., 2016

Dynamically combining climate models to -supermodel- the tropical Pacific

Shen M.L, Keenlyside N., Selten F., Wiegerinck W.A.J.J., Duane G.S., 2016

All publications by SNN

SNN Adaptive Intelligence

We conduct research on the computational principles that underlie natural and artificial intelligence. Intelligent behavior is learned by adapting to the environment; it requires integration of sensory data with prior knowledge; and it must be robust to noise.

The research goal is to provide theoretical insights, models and methods that address these issues combining methods from machine learning and neuroscience. Particular topics are approximate methods for probabilistic ′Bayesian′ inference, control theory, neural networks and data analysis. The research results are applied in diverse fields outside of science together with our spin-off company SMART Research BV.

More about SNN and SMART Research BV