An invertible neural network trained on Gaussian-process-prior samples reconstructs pseudo-PDFs from limited Ioffe-time data in closure tests, with constraints preserved but latent-dimension-dependent extrapolation.
Parton distribution functions from lattice qcd using bayes-gauss-fourier transforms
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Normalizing Flows to Reconstruct Pseudo-PDFs
An invertible neural network trained on Gaussian-process-prior samples reconstructs pseudo-PDFs from limited Ioffe-time data in closure tests, with constraints preserved but latent-dimension-dependent extrapolation.