Nanophotonic devices manipulate light at sub-wavelength scales, enabling tasks such as
light concentration, routing, and filtering. Designing these devices to achieve precise light …

This paper concerns how motor actions are neurally represented and coded. Action
planning and motor preparation can be studied using a specific type of representational …

Rethinking Innateness asks the question," What does it really mean to say that a behavior is
innate?" The authors describe a new framework in which interactions, occurring at all levels …

We introduce a path following algorithm for L 1-regularized generalized linear models. The L
1-regularization procedure is useful especially because it, in effect, selects variables …

Neural Networks presents concepts of neural-network models and techniques of parallel
distributed processing in a three-step approach:-A brief overview of the neural structure of …

The Handbook of Neural Computation is a practical, hands-on guide to the design and
implementation of neural networks used by scientists and engineers to tackle difficult and/or …

DCPS is a connectionist production system interpreter that uses distributed representations.
As a connectionist model it consists of many simple, richly interconnected neuron-like …

Training a multilayer neural net by back-propagation is slow and requires arbitrary choices
regarding the number of hidden units and layers. This paper describes an algorithm which is …

Connectionist models provide a promising alternative to the traditional computational
approach that has for several decades dominated cognitive science and artificial …

Computational psychiatry is a rapidly emerging field that uses model-based quantities to
infer the behavioral and neuronal abnormalities that underlie psychopathology. If successful …