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SUMMARY:Monte Carlo Integration and Generation with Neural Nets - Matthew 
 Klimek (Cornell University)
DTSTART:20180427T150000Z
DTEND:20180427T160000Z
UID:TALK104611@talks.cam.ac.uk
CONTACT:Francesco Coradeschi
DESCRIPTION:The general problem of Monte Carlo integration and event gener
 ation in physics is to produce a sample of points which are distributed ov
 er phase space according to some differential cross section. I will discus
 s a framework in which an artificial neural network can be trained to perf
 orm this task. This can be viewed as a generalization of standard MC techn
 iques\, such as the VEGAS algorithm. I will present the considerations tha
 t go into the architecture of the neural net\, and show results obtained f
 or a number of simple processes of relevance to particle physics.
LOCATION:Ryle Seminar Room no. 930\, Rutherford Building\, Cavendish Labor
 atory
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