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Neural-network models for event analysis are widely used in
experimental high-energy physics, star/galaxy discrimination,
control of adaptive optical systems, prediction of nuclear
properties, fast interpolation of potential energy surfaces in
chemistry, classification of mass spectra of organic compounds,
protein-structure prediction, analysis of DNA sequences, and design
of pharmaceuticals. This book, devoted to this highly
interdisciplinary research area, addresses scientists and graduate
students. The pedagogically written review articles range over a
variety of fields including astronomy, nuclear physics,
experimental particle physics, bioinformatics, linguistics, and
information processing.
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