2 citations · 2 across the 6 of their papers we have counts for
5 papers · 1 filter
Neural Network Representation of Generalized Parton Distributions (NNGPD)
Jitao Xu, Ho Jang, Zaki Panjsheeri +10
We present a neural-network-based framework for modeling generalized parton distributions, referred to as NNGPD, in which GPDs are represented as flexible functions constrained thr…
Generalized Parton Distributions from Symbolic Regression
Andrew Dotson, Zaki Panjsheeri, Anusha Reddy Singireddy +11
AI/ML informed Symbolic Regression is the next stage of scientific modeling. We utilize a highly customizable symbolic regression package ``PySR" to model the and dependenc…
Likelihood and Correlation Analysis of Compton Form Factors for Deeply Virtual Exclusive Scattering on the Nucleon
Douglas Q. Adams, Joshua Bautista, Marija Cuic +11
A likelihood analysis of the observables in deeply virtual exclusive photoproduction off a proton target, , is presented. Two processes contribute to the r…
Variational autoencoder inverse mapper for extraction of Compton form factors: Benchmarks and conditional learning
Fayaz Hossen, Douglas Adams, Joshua Bautista +8
Deeply virtual exclusive scattering processes (DVES) serve as precise probes of nucleon quark and gluon distributions in coordinate space. These distributions are derived from gene…
VAIM-CFF: A variational autoencoder inverse mapper solution to Compton form factor extraction from deeply virtual exclusive reactions
Manal Almaeen, Tareq Alghamdi, Brandon Kriesten +4
We develop a new methodology for extracting Compton form factors (CFFs) in from deeply virtual exclusive reactions such as the unpolarized DVCS cross section using a specialized in…