Machine Learning for Effective Field Theories
Project description
ML4EFT is a general open-source framework for the integration of unbinned multivariate observables into global fits of particle physics data. It makes use of machine learning regression and classification techniques to parameterise high-dimensional likelihood ratios, and can be seamlessly integrated into global analyses of, for example, the Standard Model Effective Field Theory and Parton Distribution Functions.
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