Presents a linear PDF parametrization from dimensionality-reduced neural network bases for efficient Bayesian inference, tested via multi-closure tests on synthetic deep inelastic scattering data.
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A linear PDF model for Bayesian inference
Presents a linear PDF parametrization from dimensionality-reduced neural network bases for efficient Bayesian inference, tested via multi-closure tests on synthetic deep inelastic scattering data.