4 papers
End-to-end Differentiable Calibration and Reconstruction for Optical Particle Detectors
Omar Alterkait, César Jesús-Valls, César Jesús-Valls +3
Large-scale homogeneous detectors with optical readouts are widely used in particle detection, with Cherenkov and scintillator neutrino detectors as prominent examples. Analyses in…
Panda: Self-distillation of Reusable Sensor-level Representations for High Energy Physics
Samuel Young, Kazuhiro Terao
Liquid argon time projection chambers (LArTPCs) provide dense, high-fidelity 3D measurements of particle interactions and underpin current and future neutrino and rare-event experi…
Particle Trajectory Representation Learning with Masked Point Modeling
Sam Young, Yeon-jae Jwa, Kazuhiro Terao
Effective self-supervised learning (SSL) techniques have been key to unlocking large datasets for representation learning. While many promising methods have been developed using on…
Uncertainty Propagation within Chained Models for Machine Learning Reconstruction of Neutrino-LAr Interactions
Daniel Douglas, Aashwin Mishra, Daniel Ratner +2
Sequential or chained models are increasingly prevalent in machine learning for scientific applications, due to their flexibility and ease of development. Chained models are partic…