In this talk, I will review recent work from our group on developing deep learning models for lepton–nucleus interactions. I will begin by applying generative adversarial networks (GANs) to simulate neutrino and antineutrino collisions with nucleons. Our models encompass both charged-current quasielastic and inclusive interactions of muon neutrinos with a carbon target, offering detailed...
Final-state interactions (FSI) are a significant source of systematic uncertainty in neutrino event generators, particularly for LArTPC-based experiments. These interactions occur when particles produced in the initial neutrino-nucleus collision scatter or are absorbed while exiting the nucleus, complicating event reconstruction and interpretation. While advanced models such as GiBUU offer...
