Deep Neural Networks for New Physics Searches for Dilepton Objects at the Fermilab Short Baseline Neutrino Program

I discuss the prospects for studying dark sectors beyond the standard model at the Fermilab short-baseline neutrino experiments by applying deep neural networks. Dilepton dark sector signals can be challenging to disntinguish from photon backgrounds. We apply machine learning techniques to simulated signal and backgorund events to determine the viability of these tools for BSM searches in this channel. We compare our results to traditional search strategies and find improved sensitivity.