1. Utilizing Swift-XRT Data to Identify Source Classes in Fermi Unassociated Objects Open Access Author: Pryal, Matthew Title: Utilizing Swift-XRT Data to Identify Source Classes in Fermi Unassociated Objects Area of Honors: Astronomy and Astrophysics Keywords: FermiSwiftX-raysGamma-raysData MiningMachine LearningAstrostatistics File: Download matthew_pryal_honors_thesis.pdf Thesis Supervisors: Abraham David Falcone, Thesis SupervisorAlexander Wolszczan, Thesis Honors Advisor
