Скачать или смотреть pyhf: A Pure Python Statistical Fitting Library with Tensors and Autograd |Scipy 2020| Feickert

High Energy Physics analyses are performed with statistical computations to determine the compatibility of the reported results with the existing Standard Model. In many cases, a binned, asymptotic likelihood fit is performed following a mathematical p.d.f. template called HistFactory. The pyhf library is a pure-Python implementation of that statistical model for multi-bin histogram-based analysis and asymptotic interval estimation. pyhf supports modern computational graph libraries such as TensorFlow and PyTorch to make use of features such as auto-differentiation and GPU acceleration. Additionally, pyhf's JSON model specification has enabled the first open publication of full likelihoods from an LHC experiment.

0:00 Introduction
3:29 The HistFactory statistical model
6:34 Introduction to the pyhf API
10:36 Declarative JSON model spec
13:05 Likelihood serialization and reproduction
16:04 Tensor libraries as computational backends
18:09 Automatic differentiation
19:15 Uses in physics
20:35 Summary


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