Search Results for author: Julian Collado

Found 4 papers, 2 papers with code

Deep-Learning-Based Kinematic Reconstruction for DUNE

no code implementations11 Dec 2020 Junze Liu, Jordan Ott, Julian Collado, Benjamin Jargowsky, Wenjie Wu, Jianming Bian, Pierre Baldi

To precisely reconstruct these kinematic characteristics of detected interactions at DUNE, we have developed and will present two CNN-based methods, 2-D and 3-D, for the reconstruction of final state particle direction and energy, as well as neutrino energy.

Learning to Identify Electrons

1 code implementation3 Nov 2020 Julian Collado, Jessica N. Howard, Taylor Faucett, Tony Tong, Pierre Baldi, Daniel Whiteson

We investigate whether state-of-the-art classification features commonly used to distinguish electrons from jet backgrounds in collider experiments are overlooking valuable information.

Data Analysis, Statistics and Probability High Energy Physics - Experiment High Energy Physics - Phenomenology

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