Neural network models, in addition to being of intrinsic theoretical interest, have also proved to be a useful framework in which issues in theoretical biology can be put into perspective. These issues include, amongst others, modelling the activity of the cortex and the study of protein folding. More recently, neural network models have been extensively investigated as tools for data analysis in high energy physics experiments. These workshop proceedings reflect the strongly interdisciplinary character of the field and provide an updated overview of recent developments.

Neural network models, in addition to being of intrinsic theoretical interest, have also proved to be a useful framework in which issues in theoretical biology can be put into perspective. These issues include, amongst others, modelling the activity of the cortex and the study of protein folding. More recently, neural network models have been extensively investigated as tools for data analysis in high energy physics experiments. These workshop proceedings reflect the strongly interdisciplinary character of the field and provide an updated overview of recent developments.

Neural network models, in addition to being of intrinsic theoretical interest, have also proved to be a useful framework in which issues in theoretical biology can be put into perspective. These issues include, amongst others, modelling the activity of the cortex and the study of protein folding. More recently, neural network models have been extensively investigated as tools for data analysis in high energy physics experiments. These workshop proceedings reflect the strongly interdisciplinary character of the field and provide an updated overview of recent developments.