82 citations · 170 across the 13 of their papers we have counts for
3 papers · 1 filter
Benchmarks for a Global Extraction of Information from Deeply Virtual Exclusive Scattering
Manal Almaeen, Jake Grigsby, Joshua Hoskins +4
We develop a framework to establish benchmarks for machine learning and deep neural networks analyses of exclusive scattering cross sections (FemtoNet). Within this framework we pr…
A survey of machine learning-based physics event generation
Yasir Alanazi, N. Sato, Pawel Ambrozewicz +5
Event generators in high-energy nuclear and particle physics play an important role in facilitating studies of particle reactions. We survey the state-of-the-art of machine learnin…
Simulation of electron-proton scattering events by a Feature-Augmented and Transformed Generative Adversarial Network (FAT-GAN)
Yasir Alanazi, N. Sato, Tianbo Liu +9
We apply generative adversarial network (GAN) technology to build an event generator that simulates particle production in electron-proton scattering that is free of theoretical as…