Abstract. The resolution of combinatorial optimization problems can greatly benefit from the parallel and distributed processing which is characteristic of neural network paradigm...
Randomly connected recurrent neural circuits have proven to be very powerful models for online computations when a trained memoryless readout function is appended. Such Reservoir ...
Benjamin Schrauwen, Lars Buesing, Robert A. Legens...
Stochastic resonance (SR) is fundamental to physical and biological processes. Here, we use a stochastic gain-tuning model to investigate interactions between aging-related increa...
The Noise Sensitivity Signature (NSS), originally introduced by Grossman and Lapedes (1993), was proposed as an alternative to cross validation for selecting network complexity. I...
— This paper presents a method to autonomously extract object features that describe their dynamics from active sensing experiences. The model is composed of a dynamics learning ...