# Neural network parametrization of deep inelastic structure functions

@article{Forte2002NeuralNP, title={Neural network parametrization of deep inelastic structure functions}, author={Stefano Forte and Llu{\'i}s Garrido and Jos{\'e} Ignacio Latorre and Andrea Piccione}, journal={Journal of High Energy Physics}, year={2002}, volume={2002}, pages={062-062} }

We construct a parametrization of deep-inelastic structure functions which retains information on experimental errors and correlations, and which does not introduce any theoretical bias while interpolating between existing data points. We generate a Monte Carlo sample of pseudo-data configurations and we train an ensemble of neural networks on them. This effectively provides us with a probability measure in the space of structure functions, within the whole kinematic region where data are…

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