Applications of Neural Networks in Hadron Physics

Understand

The Bayesian approach for the feed-forward neural networks is reviewed.

• Its potential for usage in hadron physics is discussed.
• As an example of the application the study of the the two-photon exchange effect is presented.
• We focus on the model comparison, the estimation of the systematic uncertainties due to the choice of the model, and the over-fitting.