Machine Learning Methods at the Intersection of Nuclear and Neutrino Physics
ORAL · APR-R87 · ID: 3994207
Presentations
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The DNA of nuclear models: How AI predicts nuclear masses
ORAL
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Publication: https://arxiv.org/abs/2508.08370
Presenters
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Kate Richardson
- Massachusetts Institute of Technology
Authors
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Kate Richardson
- Massachusetts Institute of Technology
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Sokratis Trifinopoulos
- CERN
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Mike Williams
- Massachusetts Institute of Technology
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Computer Vision for Video-Based Material Strain Extraction
ORAL
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Publication: We plan to prepare a manuscript for the AI methodology described in this talk.
Presenters
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Sonata B Simonaitis-Boyd
- University of California, San Diego
Authors
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Sonata B Simonaitis-Boyd
- University of California, San Diego
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Aobo Li
- University of California, San Diego
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Alexander F Leder
- Los Alamos National Labratory
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State space models for the Project 8 neutrino mass experiment
ORAL
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Presenters
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Hannah P Binney
- Massachusetts Institute of Technology
Authors
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Hannah P Binney
- Massachusetts Institute of Technology
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Christina Reissel
- Massachusetts Institute of Technology
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Luis Felipe Koehler Domingues
- Grinnell College
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Kyungseop Yoon
- Massachusetts Institute of Technology
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Joseph AAngelo Formaggio
- Massachusetts Institute of Technology
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Philip C Harris
- MIT
- Massachusetts Institute of Technology
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Development and testing of trigger algorithms for the Project 8 experiment
ORAL
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Presenters
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Ehteshamul Karim
- University of Pittsburgh
Authors
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Ehteshamul Karim
- University of Pittsburgh
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Event reconstruction using Graph Neural Networks in Project 8
ORAL
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Presenters
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Vivek Sharma
- University of Pittsburgh
Authors
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Vivek Sharma
- University of Pittsburgh
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A 3+1 Sterile Neutrino Global Fit using Simulation-Based Inference
ORAL
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Publication: Joshua Villarreal et al 2025 Mach. Learn.: Sci. Technol. 6 035053 "A frequentist simulation-based inference treatment of sterile neutrino global fits"
Presenters
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Julia P Woodward
- Massachusetts Institute of Technology
Authors
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Julia P Woodward
- Massachusetts Institute of Technology
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Physics Informed Neural Network (PINN) and Spherical Harmonic–PINN Approaches for B0 field reconstruction in the LANL nEDM Experiment
ORAL
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Presenters
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Prakash Adhikari
- University of Kentucky
Authors
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Prakash Adhikari
- University of Kentucky
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The Texas Automated Particle Identification Routine (TAPIR)
ORAL
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Presenters
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Bryan M Harvey
- Texas A&M University College Station
Authors
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Bryan M Harvey
- Texas A&M University College Station
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Luke Knull
- Iowa State University
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Travis Hankins
- Texas A&M University College Station
- Texas A&M University, Cyclotron Institute
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Mike D Youngs
- Texas A&M University College Station
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Kris Hagel
- Texas A&M University Cyclotron Institute
- Texas A&M University, Cyclotron Institute
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Alan B McIntosh
- Advisor
- Texas A&M University, Cyclotron Institute
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Sherry J Yennello
- Texas A&M University College Station
- Texas A&M University, College Station
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