scholarly journals The Use of Neural Networks in High-Energy Physics

1993 ◽  
Vol 5 (4) ◽  
pp. 505-549 ◽  
Author(s):  
Bruce Denby

In the past few years a wide variety of applications of neural networks to pattern recognition in experimental high-energy physics has appeared. The neural network solutions are in general of high quality, and, in a number of cases, are superior to those obtained using "traditional'' methods. But neural networks are of particular interest in high-energy physics for another reason as well: much of the pattern recognition must be performed online, that is, in a few microseconds or less. The inherent parallelism of neural network algorithms, and the ability to implement them as very fast hardware devices, may make them an ideal technology for this application.

1992 ◽  
Vol 03 (04) ◽  
pp. 733-771 ◽  
Author(s):  
C. BORTOLOTTO ◽  
A. DE ANGELIS ◽  
N. DE GROOT ◽  
J. SEIXAS

During the last years, the possibility to use Artificial Neural Networks in experimental High Energy Physics has been widely studied. In particular, applications to pattern recognition and pattern classification problems have been investigated. The purpose of this article is to review the status of such investigations and the techniques established.


1992 ◽  
Vol 03 (supp01) ◽  
pp. 243-254 ◽  
Author(s):  
P. Mazzanti ◽  
R. Odorico

A short survey of the use of neural networks and statistical discriminants in high energy physics for recognition of heavy flavor jets is presented. After illustrating the various neural and statistical classifiers currently used, some assessment of their comparative performance for top and bottom jets is made.


2016 ◽  
Vol 93 (9) ◽  
Author(s):  
Pierre Baldi ◽  
Kevin Bauer ◽  
Clara Eng ◽  
Peter Sadowski ◽  
Daniel Whiteson

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