This paper aims to propose an extension of SOMs called an “SOM of SOMs,” or SOM¾ , in which the mapped objects are self-organizing maps themselves. In SOM¾ , each nodal unit ...
Models of associative memory usually have full connectivity or if diluted, random symmetric connectivity. In contrast, biological neural systems have predominantly local, non-symm...
In this paper we propose an approach to variable selection that uses a neural-network model as the tool to determine which variables are to be discarded. The method performs a bac...
We investigate a form of modular neural network for classification with (a) pre-separated input vectors entering its specialist (expert) networks, (b) specialist networks which ar...
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...