Minisymposium: Applications of Advanced Statistics and Machine Learning Methods in Nuclear Physics III
ORAL · L08 · ID: 1738516
Presentations
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Towards Automation for γ-Ray Spectroscopy
ORAL
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Presenters
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Tamas A Budner
- Argonne National Laboratory
Authors
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Tamas A Budner
- Argonne National Laboratory
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David Lenz
- Argonne National Laboratory
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Michael P Carpenter
- Argonne National Laboratory
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Sven Leyffer
- Argonne National Laboratory
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Filip G Kondev
- Argonne National Laboratory
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Amel Korichi
- Université Paris-Saclay
- IJCLab, Argonne National Laboratory
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Torben Lauritsen
- Argonne National Laboratory
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Thomas F Lynn
- Argonne National Laboratory
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Marco Siciliano
- ANL
- Argonne National Laboratory
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Machine learning based design optimization for the search of neutrinoless double-beta decay with LEGEND
ORAL
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Presenters
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Ann-Kathrin Schuetz
- Lawrence Berkeley National Laboratory
Authors
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Ann-Kathrin Schuetz
- Lawrence Berkeley National Laboratory
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Using Convolutional Neural Networks to Classify Scintillator Data
ORAL
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Presenters
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Adam Hartley
- Michigan State University
- FRIB
Authors
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Adam Hartley
- Michigan State University
- FRIB
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Sean N Liddick
- Michigan State University
- FRIB
- FRIB/NSCL
- Facility for Rare Isotope Beams, Michigan State University, East Lansing, MI 48824, USA
- FRIB/MSU
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Geir Ulvik
- University of Oslo
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Morten Hjorth-Jensen
- Michigan State University
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Aaron Chester
- Michigan State University
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CARIBU-matic and the MUSIC ML project: examples of machine-learning applications for beam tuning and experimental data analysis/classification
ORAL
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Publication: [1] K. Raghavan, M.L. Avila, P. Balaprakash, H. Jayatissa, D. Santiago-Gonzalez, "Classification of events from α-induced reactions in the MUSIC detector via statistical and ML methods", https://arxiv.org/abs/2204.03137
Presenters
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Daniel Santiago-Gonzalez
- Argonne National Laboratory
Authors
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Daniel Santiago-Gonzalez
- Argonne National Laboratory
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Melina Avila
- Argonne National Laboratory
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Prasanna Balaprakash
- Oak Ridge National Laboratory
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Heshani Jayatissa
- Argonne National Laboratory
- Los Alamos National Laboratory
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Krishnan Raghavan
- Argonne National Laboratory
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Nathan Callahan
- Argonne National Laboratory
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Offline reinforcement learning for closed-loop control of the VENUS ion source
ORAL
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Presenters
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Yue Shi Lai
- Lawrence Berkeley National Laboratory
Authors
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Yue Shi Lai
- Lawrence Berkeley National Laboratory
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Atomic Masses with Machine Learning for the Astrophysical R-process
ORAL
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Presenters
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Mengke Li
- Clemson University
Authors
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Mengke Li
- Clemson University
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Trevor M Sprouse
- Los Alamos National Laboratory
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Bradley S Meyer
- Clemson University
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Matthew R Mumpower
- LANL
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Machine learning assisted filtering approach for ion source optimization and control
ORAL
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Presenters
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victor watson
- Lawrence Berkeley National Laboratory
Authors
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victor watson
- Lawrence Berkeley National Laboratory
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Heather L Crawford
- Lawrence Berkeley National Laboratory
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Marco Salathe
- Lawrence Berkeley National Laboratory
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Damon Todd
- Lawrence Berkeley National Laboratory
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Quantifying uncertainty of nuclear properties within machine learning frameworks
ORAL
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Presenters
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Mengyao Huang
- Lawrence Livermore National Laboratory
Authors
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Mengyao Huang
- Lawrence Livermore National Laboratory
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Kyle A Wendt
- Lawrence Livermore Natl Lab
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Nicolas F Schunck
- Lawrence Livermore National Laboratory
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Xiao Chen
- Lawrence Livermore National Laboratory
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