Bayesian Learning of Neural Networks for Signal/Background Discrimination in Particle Physics

Pogwizd, Michael; Elgass, Laura Jane; Bhat, Pushpalatha C.

Bayesian Learning of Neural Networks for Signal/Background Discrimination in Particle Physics

Authors

Pogwizd, Michael

Elgass, Laura Jane

Bhat, Pushpalatha C.

Description

Neural networks are used extensively in classification problems in particle physics research. Since the training of neural networks can be viewed as a problem of inference, Bayesian learning of neural networks can provide more optimal and robust results than conventional learning methods. We have investigated the use of Bayesian neural networks for signal/background discrimination in the search for second generation leptoquarks at the Tevatron, as an example. We present a comparison of the results obtained from the conventional training of feedforward neural networks and networks trained with Bayesian methods.
3 pages, 4 figures, conference proceedings