Tootfinder

This https://arxiv.org/abs/2402.08151 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Perturbative partial moment matching and gradient-flow adaptive importance sampling transformations for Bayesian leave one out cross-validation
Importance sampling (IS) allows one to approximate leave one out (LOO) cross-validation for a Bayesian model, without refitting, by inverting the Bayesian update equation to subtract a given data point from a model posterior. For each data point, one computes expectations under the corresponding LOO posterior by weighted averaging over the full data posterior. This task sometimes requires weight stabilization in the form of adapting the posterior distribution via transformation. So long as one …

Window observables for benchmarking parton distribution functions
Joe Karpie, Christopher J. Monahan, Kostas Orginos, Savvas Zafeiropoulos
https://arxiv.org/abs/2505.22795

Window observables for benchmarking parton distribution functions
Global analysis of collider and fixed-target experimental data and calculations from lattice quantum chromodynamics (QCD) are used to gain complementary information on the structure of hadrons. We propose novel ``window observables'' that allow for higher precision cross-validation between the different approaches, a critical step for studies that wish to combine the datasets. Global analyses are limited by the kinematic regions accessible to experiment, particularly in a range of Bjorken-$x$, …