Mini-Conference: Machine Learning in Plasma Sciences I
FOCUS · NM10 · ID: 21926
Presentations
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Welcome Remarks
COFFEE_KLATCH
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Automation and control of laser wakefield accelerators using Bayesian optimization
ORAL
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Publication: R. J. Shalloo et al., "Automation and control of laser wakefield accelerators using Bayesian optimization", Nat. Comms. 11, 6355 (2020)<br>https://doi.org/10.1038/s41467-020-20245-6
Presenters
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Rob Shalloo
DESY
Authors
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Rob Shalloo
DESY
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Stephen J Dann
STFC Central Laser Facility, Central Laser Facility, The Cockcroft Institute
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Jan-Niclas Gruse
Imperial College London
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Christopher Underwood
University of York
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Andre F Antoine
University of Michigan
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Christopher Arran
University of York
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Michael Backhouse
Imperial College London
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Christopher Baird
Rutherford Appleton Lab, Central Laser Facility
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Mario Balcazar
University of Michigan
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Nicholas Bourgeois
STFC Central Laser Facility, Central Laser Facility, Rutherford Appleton Lab
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Jason A Cardarelli
University of Michigan
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Peter W Hatfield
University of Oxford
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Jiwoong Kang
University of Michigan
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Karl M Krushelnick
University of Michigan, Center for Ultra-Fast Optics, University of Michigan, Ann Arbor, Michigan USA, University of Michigan - Ann Arbor, Gérard Mourou Center for Ultrafast Optical Science, University of Michigan, Ann Arbor, Michigan 48109, USA
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Stuart P.D. Mangles
Imperial College London
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Chris D Murphy
University of York
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Ning Lu
University of Michigan
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Jens Osterhoff
Deutsches Elektronen-Synchrotron DESY, DESY, Deutsches Elektronen-Synchrotron (DESY)
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Kristjan Poder
Deutsches Elektronen-Synchrotron (DESY)
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Pattathil Rajeev
Rutherford Appleton Lab, Central Laser Facility
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Christopher P Ridgers
University of York
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Savio V Rozario
Imperial College London
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Matthew P Selwood
University of York
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Ashwin J Shahani
University of Michigan
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Dan R Symes
STFC Central Laser Facility, Central Laser Facility
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Alexander G Thomas
University of Michigan, University of Michigan - Ann Arbor
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Christopher Thornton
Central Laser Facility
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Zulfikar Najmudin
Imperial College London, Imperial College London, UK
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Matthew J. V Streeter
Queen's University Belfast, The Queens University of Belfast, The Cockcroft Institute
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Bayesian Methods in Inertial Confinement Fusion Research: Embracing uncertainty and Learning More from our Data*
ORAL
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Presenters
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Patrick F Knapp
Sandia National Laboratories
Authors
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Patrick F Knapp
Sandia National Laboratories
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Michael E Glinsky
Sandia National Laboratories
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William E Lewis
Sandia National Laboratories
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Machine Learning Spike Trains of Uneven Duration and Delay: STUD Pulses for Laser-Plasma Instability Control and Suppression
ORAL
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Presenters
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Bedros B Afeyan
Polymath Research Inc
Authors
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Bedros B Afeyan
Polymath Research Inc
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Jeffrey A Hittinger
Lawrence Livermore Natl Lab, LLNL
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Jayaraman J Thiagarajan
LLNL, Lawrence Livermore National Laboratory
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Rushil Anirudh
LLNL, Lawrence Livermore National Laboratory
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Data-driven modelling of laser-plasma experiments enabled by large datasets.
ORAL
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Presenters
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Andre F Antoine
University of Michigan
Authors
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Andre F Antoine
University of Michigan
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Alexander G Thomas
University of Michigan, University of Michigan - Ann Arbor
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Jason A Cardarelli
University of Michigan
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Matthew J. V Streeter
Queen's University Belfast, The Queens University of Belfast, The Cockcroft Institute
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Chris D Murphy
University of York
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Karl M Krushelnick
University of Michigan, Center for Ultra-Fast Optics, University of Michigan, Ann Arbor, Michigan USA, University of Michigan - Ann Arbor, Gérard Mourou Center for Ultrafast Optical Science, University of Michigan, Ann Arbor, Michigan 48109, USA
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Christopher Arran
University of York
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Stuart P.D. Mangles
Imperial College London
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Zulfikar Najmudin
Imperial College London, Imperial College London, UK
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Archis Joglekar
Polymath Research Inc
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Mario Balcazar
University of Michigan
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Peter W Hatfield
University of Oxford
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Nicholas Bourgeois
STFC Central Laser Facility, Central Laser Facility, Rutherford Appleton Lab
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Stephen J Dann
STFC Central Laser Facility, Central Laser Facility, The Cockcroft Institute
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Jan-Niclas Gruse
Imperial College London
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Daniel R Symes
Rutherford Appleton Lab
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Christopher P Ridgers
University of York
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Ashwin J Shahani
University of Michigan
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Rob Shalloo
DESY
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Savio V Rozario
Imperial College London
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Kristjan Poder
Imperial College London
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Jens Osterhoff
Deutsches Elektronen-Synchrotron DESY, DESY, Deutsches Elektronen-Synchrotron (DESY)
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Matthew P Selwood
University of York
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Michael Backhouse
Imperial College London
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Christopher Underwood
University of York
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Jiwoong Kang
University of Michigan
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Pattathil Rajeev
Rutherford Appleton Lab, Central Laser Facility
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Christopher Baird
Rutherford Appleton Lab, Central Laser Facility
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Ning Lu
University of Michigan
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What machine learning can and cannot do for ICF
ORAL
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Presenters
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Baolian Cheng
Los Alamos Natl Lab
Authors
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Baolian Cheng
Los Alamos Natl Lab
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Optimizing high energy density experimental designs to elucidate complex coupling between physics phenomena for training ML models
ORAL
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Presenters
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John L Kline
Los Alamos Natl Lab, Los Alamos National Laboratory
Authors
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John L Kline
Los Alamos Natl Lab, Los Alamos National Laboratory
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Michael J Grosskopf
Los Alamos National Lab, Los Alamos National Laboratory
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Nelson M Hoffman
Los Alamos National Laboratory, Los Alamos Natl Lab
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Bedros B Afeyan
Polymath Research Inc
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Neural Networks for Rapid Analysis of High Repetition Rate Diagnostics
ORAL
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Publication: D.A. Mariscal, et al., "Design of Flexible Proton Beam Imaging Energy Spectrometers (PROBIES)", Plasma Physics and Controlled Fusion, (submitted)
Presenters
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Derek Mariscal
Lawrence Livermore Natl Lab, Lawrence Livermore National Laboratory
Authors
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Derek Mariscal
Lawrence Livermore Natl Lab, Lawrence Livermore National Laboratory
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Multi-Output Surrogate Construction for Fusion Simulations
ORAL
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Presenters
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Kathryn Maupin
Authors
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Kathryn Maupin
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Anh Tran
Sandia National Laboratories
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Michael E Glinsky
Sandia National Laboratories
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Patrick F Knapp
Sandia National Laboratories
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William E Lewis
Sandia National Laboratories
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Improving the plasma science data environment
ORAL
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Presenters
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Nicholas Murphy
Center for Astrophysics | Harvard & Smithsonian, Harvard - Smithsonian Center for Astroph, Center for Astrophysics | Harvard & Smithsonian, US
Authors
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Nicholas Murphy
Center for Astrophysics | Harvard & Smithsonian, Harvard - Smithsonian Center for Astroph, Center for Astrophysics | Harvard & Smithsonian, US
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Reducing Economic Costs as an Explicit Requirement for Machine-Learning-Based Classifiers
ORAL
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Presenters
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Matthew S Parsons
Pennsylvania State University
Authors
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Matthew S Parsons
Pennsylvania State University
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