Pricing Derivatives by Path Integral and Neural Networks
  Recent progress in the development of efficient computational algorithms to price financial derivatives is summarized. A first algorithm is based on a path integral approach to option pricing, while a second algorithm makes use of a neural network parameterization of option prices. The accuracy of the two methods is established from comparisons with the results of the standard procedures used in quantitative finance. 
G. Montagna, M. Morelli, O. Nicrosini, P. Amato and M. Farina