Information and Statistics for Nuclear Experiment and Theory workshop (ISNET-9)

US/Central
Washington University in St. Louis

Washington University in St. Louis

1 Brookings Dr, St. Louis, MO 63130
Description

The next international meeting on Information and Statistics in Nuclear Experiment and Theory (ISNET-9), organized by the Department of Physics at Washington University in St. Louis, will take place May 22-26, 2023 in St. Louis, Missouri. 

The mission of the ISNET community is to encourage, facilitate and develop the use of statistical and computational methodologies to enable nuclear physics to reach more quantitatively rigorous scientific conclusions. We do this by combining domain knowledge from the broad nuclear physics community with expertise in related fields of research, such as statistics, mathematics and computer science.

For 2023, ISNET-9 will be a hybrid meeting. Talks will be delivered on-site, but sessions will also be broadcast via Zoom for remote participants. Talks will take place beginning Tuesday morning the 23rd and continue through the morning of Friday the 26th

On Monday, May 22nd, we will also host the third annual BAND Camp. BAND Camp is a one-day set of pedagogical presentations organized by the Bayesian Analysis of Nuclear Dynamics collaboration (https://bandframework.github.io). Talks will be geared towards students and postdocs, and aim to provide an introduction to the software tools developed by BAND and to the corresponding concepts and methods of Bayesian uncertainty quantification. This year BAND is accepting 40 participants for an in-person camp; registrations will be accepted until that capacity is exhausted. 

On Wednesday, May 24th, we will hold a one-day machine learning symposium in honor of John Clark (Wayman Crow Professor Emeritus of Physics at WashU) to recognize his pioneering work in neural networks.

There are no conference fees for ISNET-9. A welcome reception is planned for Monday, a dinner is planned for Wednesday evening, and a poster session is planned for Thursday afternoon.

Topics:

  • Statistical methods for optimization and data analysis
  • Bayesian inference
  • Uncertainty quantification
  • Machine learning
  • Emulators
  • Resampling techniques
  • Accelerator design

 

Local Organizing Committee:

 

This conference is supported by the McDonnell Center for the Space Sciences, the Department of Physics, and the School of Arts & Sciences at Washington University in St. Louis. BAND Camp is supported by the BAND collaboration.

    • BAND Camp: Registration/Breakfast Compton 241/245

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    • BAND Camp: Session I Whitaker 218

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      • 1
        Welcome and Intro Whitaker 218 (Washington University in St. Louis )

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        Speaker: Maria Piarulli (Washington University)
      • 2
        Gaussian Process emulation using surmise Whitaker 218

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        Speakers: Moses Chan (Northwestern), Özge Surer (Miami University)
    • 10:45 AM
      Coffee Break Compton 241/245

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    • BAND Camp: Session II
    • 12:45 PM
      Lunch Break Compton 241/245

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    • BAND Camp: Session III Whitaker 218 (Washington University in ST. Louis )

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    • 3:45 PM
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    • BAND Camp: Session IV Whitaker 218

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    • Welcome Reception Women’s Building, Ann W. Olin

      Women’s Building, Ann W. Olin

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    • 8:00 AM
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    • ISNET: Welcome Crow 201

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      Convener: Brad Jolliff (Washington University)
    • ISNET: Statistical methods for optimization, Bayesian inference, and uncertainty quantification Crow 201

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      • 7
        Recent tools and developments in Bayesian statistics
        Speaker: Yuling Yao (Flatiron Institute)
      • 8
        A statistical exploration of CEMP star classification with s-process models
        Speaker: Andrés Yagüe López (Los Alamos National Lab)
      • 9
        Global fits and Bayesian inference in "Beyond the Standard Model" physics (virtual)
        Speaker: Anders Kvellestad (University of Oslo)
    • 10:30 AM
      Coffee Break Compton 241/245

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    • ISNET: Statistical methods for optimization, Bayesian inference, and uncertainty quantification Crow 201

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      • 10
        Applications of novel chiral interactions to quantum Monte Carlo methods and astrophysical data analysis
        Speaker: Rahul Somasundaram (Syracuse University)
      • 11
        Sequential Bayesian experimental design for calibration of expensive physics models
        Speaker: Ozge Sürer
      • 12
        History matching for nuclear ab initio calculations
        Speaker: Christian Forssén (Durham University)
    • 12:30 PM
      Lunch Break Compton 241/245

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    • ISNET: Statistical methods for optimization, Bayesian inference, and uncertainty quantification Crow 201

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      • 13
        Bayesian probability updates using sampling/importance resampling: applications in nuclear theory
        Speaker: Weiguang Jiang (Chalmers University)
      • 14
        Hamiltonian Monte Carlo computation in spatial statistics
        Speaker: Debashis Mondal (WashU)
      • 15
        Bayesian model calibration for nuclear decays with the Skyrme finite-amplitude method
        Speaker: Tong Li (LLNL)
    • 3:00 PM
      Coffee Break Compton 241/245

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    • ISNET: Statistical methods for optimization, Bayesian inference, and uncertainty quantification Crow 201

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    • Discussion Session Crow 201

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    • 8:25 AM
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    • ISNET: Symposium in Honor of John Clark: Different Aspects of Machine Learning Crow 201

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    • 10:30 AM
      Coffee Break Compton 241/245 (Washington University in St. Louis )

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    • ISNET: Symposium in Honor of John Clark: Different Aspects of Machine Learning Crow 201

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    • 12:15 PM
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    • ISNET: Symposium in Honor of John Clark: Different Aspects of Machine Learning Crow 201

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      • 25
        Nuclear masses learned from a probabilistic neural network
        Speaker: Amy Lovell (Los Alamos National Lab)
      • 26
        Machine learning for the many-body problem
        Speaker: Alessandro Lovato (Argonne National laboratory)
      • 27
        Mapping out the thermodynamic stability of a QCD EOS with a critical point using active learning
        Speaker: Debora Mroczek (University of Illinois)
    • 2:45 PM
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    • ISNET: Symposium in Honor of John Clark: Different Aspects of Machine Learning Crow 201

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      • 28
        Predicting nuclear masses with product-unit networks (virtual)
        Speaker: Babette Dellen
      • 29
        Machine learning for Deeply Virtual Compton Scattering (virtual)
        Speaker: Manal Almaeen
      • 30
        Short Talk: Deep learning pairing correlations from neural-network quantum states
        Speaker: Jane Kim
    • Discussion Session Crow 201

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    • Social Dinner The Boathouse at Forest Park

      The Boathouse at Forest Park

      6101 Government Dr, St. Louis, MO 63110, United States
    • 8:30 AM
      Breakfast Compton 241/245

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    • ISNET: Emulators and Resampling Techniques Crow 201

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    • 10:30 AM
      Coffee Break Compton 241/245

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    • ISNET: Emulators and Resampling Techniques Crow 201

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      • 34
        Multi-output gaussian processes for inverse uncertainty quantification in neutron noise analysis (virtual)
        Speaker: Paul Lartaud
      • 35
        Quantification for a covariant energy density functional emulated by the reduced basis method
        Speaker: Pablo Giuliani (Michigan State University)
      • 36
        Hamiltonian Monte Carlo & eigenvector continuation for ab initio nuclear physics
        Speaker: Andreas Ekström (Chalmers University of Technology)
    • 12:30 PM
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    • ISNET: Emulators and Resampling Techniques Crow 201

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      • 37
        Eigenvector continuation emulators for the ab initio symmetry-adapted framework
        Speaker: Kevin Becker
      • 38
        Bootstrap for multivariate time series and gravitational wave detection
        Speaker: Soumen Lahiri (Washington University)
      • 39
        Data integration using constrained Gaussian process models with applications to nuclear physics
        Speaker: Shuang Zhou (Arizona State University)
    • 3:00 PM
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    • ISNET: Emulators and Resampling Techniques Crow 201

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      • 40
        Short Talk: Potential energy surface emulation and impact on fission trajectories
        Speaker: Daniel Lay
      • 41
        Short Talk: Ex fissio ad astra: extending optical models to the fission fragment region
        Speaker: Kyle Beyer
      • 42
        Short Talk: Reduced Basis Methods and Scattering
        Speaker: Daniel Odell
    • Discussion Session Crow 201

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    • ISNET: Poster Session

      Andrew Gordeev: Bayesian parameter estimation of QGP viscosities in partial chemical equilibrium
      Denielle Ricciardi: Accounting for material and experimental variability using a random effects bayesian inferential framework
      Hannah Göttling: Gaussian processes for the nuclear equation of state
      Mookyong Son: Variational Bayes Computer Models
      Yehu Chen: Active learning for marginal effect estimation with Gaussian Process preference learning

    • 8:30 AM
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    • ISNET: Advanced Statistics Techniques for Analyzing Experimental Data and for Accelerator design Crow 201

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      • 43
        AI/ML+data science tools for detector design at the Electron Ion Collider (virtual)
        Speaker: Cristiano Fanelli (William & Mary)
      • 44
        Excavating insights from sparse data with statistics and machine learning
        Speaker: Kyle Godbey
      • 45
        Gaussian processes for autonomous data acquisition at large-scale synchrotron and neutron facilities
        Speaker: Marcus Noack (Lawrence Berkeley National Laboratory)
    • 10:30 AM
      Coffee Break Compton 241/245

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    • ISNET: Advanced Statistics Techniques for Analyzing Experimental Data and for Accelerator design Crow 201

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      • 46
        Deep learning techniques in ground-based imaging gamma-ray observatories (virtual)
        Speaker: Daniel Nieto (Madrid University)
    • Discussion Session: Closing/Remarks Crow 201

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