Nuclear Structure Function F₂^A Calculated by Neural Network

Neural Networks have been increasingly utilized for training with data to calculate quantities of interest. In Nuclear and Particle Physics, the nuclear structure function F₂^A is of interest for providing information on the quark content of nuclei, and is also useful for systematics in various analyses. The goal of this project is an AI based code that can provide representative calculations for F₂^A. This talk will provide details on the setup, running, and initial results from inclAI.