Name: Information and Statistics for Nuclear Experiment and Theory workshop (ISNET-9)
Start: 2023-05-22T08:00:00-05:00
End: 2023-05-26T13:30:00-05:00
Location: Washington University in St. Louis

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

from Monday, 22 May 2023 (08:00) to Friday, 26 May 2023 (13:30)

Monday, 22 May 2023

08:00 Registration/Breakfast
Registration/Breakfast
08:00 - 09:00
Room: Compton 241/245
09:00 Session I
Session I
09:00 - 10:45
Room: Whitaker 218
Contributions

09:00 Welcome and Intro - Maria Piarulli (Washington University)

09:05 Gaussian Process emulation using surmise - Moses Chan (Northwestern) Özge Surer (Miami University)
10:45 Coffee Break
Coffee Break
10:45 - 11:15
Room: Compton 241/245
11:15 Session II
Session II
11:15 - 12:45
Contributions

11:15 Reduced Basis Methods for emulation and the ROSE software package - Daniel Odell (Ohio) Pablo Giuliani (MSU/FRIB)
12:45 Lunch Break
Lunch Break
12:45 - 14:15
Room: Compton 241/245
14:15 Session III
Session III
14:15 - 15:45
Room: Whitaker 218
Contributions

14:15 Bayesian Model Mixing using Taweret - Alexandra Semposki (Ohio University) John Yannotty (Ohio State) Matt Pratola (Ohio State)
15:45 Coffee Break
Coffee Break
15:45 - 16:15
Room: Compton 241/245
16:15 Session IV
Session IV
16:15 - 17:30
Room: Whitaker 218
Contributions

16:15 The Bayesian Mass Explorer, BMEX - Kyle Godbey (MSU/FRIB)

16:55 Experimental Design and the BAND software framework - Dick Furnstahl (Ohio State) Witek Nazarewicz (MSU/FRIB)
18:00

18:00 - 20:00
Room: Women’s Building, Ann W. Olin
Tuesday, 23 May 2023

08:00 Registration/Breakfast
Registration/Breakfast
08:00 - 08:45
Room: Crow 201/Compton 241/245

08:45 Welcome
Welcome
08:45 - 09:00
Room: Crow 201
09:00 Statistical methods for optimization, Bayesian inference, and uncertainty quantification
Statistical methods for optimization, Bayesian inference, and uncertainty quantification
09:00 - 10:30
Room: Crow 201
Contributions

09:00 Recent tools and developments in Bayesian statistics - Yuling Yao (Flatiron Institute)

09:30 A statistical exploration of CEMP star classification with s-process models - Andrés Yagüe López (Los Alamos National Lab)

10:00 Global fits and Bayesian inference in "Beyond the Standard Model" physics (virtual) - Anders Kvellestad (University of Oslo)
10:30 Coffee Break
Coffee Break
10:30 - 11:00
Room: Compton 241/245
11:00 Statistical methods for optimization, Bayesian inference, and uncertainty quantification
Statistical methods for optimization, Bayesian inference, and uncertainty quantification
11:00 - 12:30
Room: Crow 201
Contributions

11:00 Applications of novel chiral interactions to quantum Monte Carlo methods and astrophysical data analysis - Rahul Somasundaram (Syracuse University)

11:30 Sequential Bayesian experimental design for calibration of expensive physics models - Ozge Sürer

12:00 History matching for nuclear ab initio calculations - Christian Forssén (Durham University)
12:30 Lunch Break
Lunch Break
12:30 - 13:30
Room: Compton 241/245
13:30 Statistical methods for optimization, Bayesian inference, and uncertainty quantification
Statistical methods for optimization, Bayesian inference, and uncertainty quantification
13:30 - 15:00
Room: Crow 201
Contributions

13:30 Bayesian probability updates using sampling/importance resampling: applications in nuclear theory - Weiguang Jiang (Chalmers University)

14:00 Hamiltonian Monte Carlo computation in spatial statistics - Debashis Mondal (WashU)

14:30 Bayesian model calibration for nuclear decays with the Skyrme finite-amplitude method - Tong Li (LLNL)
15:00 Coffee Break
Coffee Break
15:00 - 15:30
Room: Compton 241/245
15:30 Statistical methods for optimization, Bayesian inference, and uncertainty quantification
Statistical methods for optimization, Bayesian inference, and uncertainty quantification
15:30 - 16:30
Room: Crow 201
Contributions

15:30 Accounting for material and experimental variability using a random effects Bayesian inferential framework - Denielle Ricciardi (Sandia National Laboratories)

16:00 Short talk: Bayesian calibration of viscous anisotropic hydrodynamic simulations of heavy-ion collisions - Dananjaya Liyanage

16:15 Short Talk: How Uncertain Am I? Theoretical errors in Bayesian model calibration for EFTs - Jason Bub
16:30

16:30 - 17:00
Room: Crow 201
Wednesday, 24 May 2023

08:25 Breakfast
Breakfast
08:25 - 08:55
Room: Crow 201/Compton 241/245
08:55 Symposium in Honor of John Clark: Different Aspects of Machine Learning
Symposium in Honor of John Clark: Different Aspects of Machine Learning
08:55 - 10:30
Room: Crow 201
Contributions

08:55 Prof. John W. Clark - Henric Krawczynski

09:00 John Clark: Physicist at the computational frontier (virtual) - Henrik Bohr

09:45 Machine learning for nuclear physics - Witek Nazarewicz (MSU/FRIB)
10:30 Coffee Break
Coffee Break
10:30 - 11:00
Room: Compton 241/245
11:00 Symposium in Honor of John Clark: Different Aspects of Machine Learning
Symposium in Honor of John Clark: Different Aspects of Machine Learning
11:00 - 12:15
Room: Crow 201
Contributions

11:00 Machine learning of nuclear properties : a brief tribute to Prof. John Walter Clark (recording) - Eirene Mavrommatis

11:15 Surrogate models of nuclear density functional theory with gaussian processes and autoencoders - Marc Verriere

11:45 Machine learning for heavy-ion accelerators (virtual) - Yue Hao (Michigan State University)
12:15 Lunch Break
Lunch Break
12:15 - 13:15
Room: Compton 241/245
13:15 Symposium in Honor of John Clark: Different Aspects of Machine Learning
Symposium in Honor of John Clark: Different Aspects of Machine Learning
13:15 - 14:45
Room: Crow 201
Contributions

13:15 Nuclear masses learned from a probabilistic neural network - Amy Lovell (Los Alamos National Lab)

13:45 Machine learning for the many-body problem - Alessandro Lovato (Argonne National laboratory)

14:15 Mapping out the thermodynamic stability of a QCD EOS with a critical point using active learning - Debora Mroczek (University of Illinois)
14:45 Coffee Break
Coffee Break
14:45 - 15:15
Room: Compton 241/245
15:15 Symposium in Honor of John Clark: Different Aspects of Machine Learning
Symposium in Honor of John Clark: Different Aspects of Machine Learning
15:15 - 16:30
Room: Crow 201
Contributions

15:15 Predicting nuclear masses with product-unit networks (virtual) - Babette Dellen

15:45 Machine learning for Deeply Virtual Compton Scattering (virtual) - Manal Almaeen

16:15 Short Talk: Deep learning pairing correlations from neural-network quantum states - Jane Kim
16:30

16:30 - 17:00
Room: Crow 201

18:00

18:00 - 21:00
Room: The Boathouse at Forest Park
Thursday, 25 May 2023

08:30 Breakfast
Breakfast
08:30 - 09:00
Room: Compton 241/245
09:00 Emulators and Resampling Techniques
Emulators and Resampling Techniques
09:00 - 10:30
Room: Crow 201
Contributions

09:00 Overview of emulators for nuclear physics - Dick Furnstahl

09:30 Known Boundary Emulation (virtual) - Ian Vernon

10:00 Gaussian process regression constrained by boundary value problems - Mamikon Gulian (Sandia National Laboratories)
10:30 Coffee Break
Coffee Break
10:30 - 11:00
Room: Compton 241/245
11:00 Emulators and Resampling Techniques
Emulators and Resampling Techniques
11:00 - 12:30
Room: Crow 201
Contributions

11:00 Multi-output gaussian processes for inverse uncertainty quantification in neutron noise analysis (virtual) - Paul Lartaud

11:30 Quantification for a covariant energy density functional emulated by the reduced basis method - Pablo Giuliani (Michigan State University)

12:00 Hamiltonian Monte Carlo & eigenvector continuation for ab initio nuclear physics - Andreas Ekström (Chalmers University of Technology)
12:30 Lunch Break
Lunch Break
12:30 - 13:30
Room: Compton 241/245
13:30 Emulators and Resampling Techniques
Emulators and Resampling Techniques
13:30 - 15:00
Room: Crow 201
Contributions

13:30 Eigenvector continuation emulators for the ab initio symmetry-adapted framework - Kevin Becker

14:00 Bootstrap for multivariate time series and gravitational wave detection - Soumen Lahiri (Washington University)

14:30 Data integration using constrained Gaussian process models with applications to nuclear physics - Shuang Zhou (Arizona State University)
15:00 Coffee Break
Coffee Break
15:00 - 15:30
Room: Compton 241/245
15:30 Emulators and Resampling Techniques
Emulators and Resampling Techniques
15:30 - 16:15
Room: Crow 201
Contributions

15:30 Short Talk: Potential energy surface emulation and impact on fission trajectories - Daniel Lay

15:45 Short Talk: Ex fissio ad astra: extending optical models to the fission fragment region - Kyle Beyer

16:00 Short Talk: Reduced Basis Methods and Scattering - Daniel Odell
16:15

16:15 - 16:45
Room: Crow 201

16:45

16:45 - 17:45
Friday, 26 May 2023

08:30 Breakfast
Breakfast
08:30 - 09:00
Room: Compton 241/245
09:00 Advanced Statistics Techniques for Analyzing Experimental Data and for Accelerator design
Advanced Statistics Techniques for Analyzing Experimental Data and for Accelerator design
09:00 - 10:30
Room: Crow 201
Contributions

09:00 AI/ML+data science tools for detector design at the Electron Ion Collider (virtual) - Cristiano Fanelli (William & Mary)

09:30 Excavating insights from sparse data with statistics and machine learning - Kyle Godbey

10:00 Gaussian processes for autonomous data acquisition at large-scale synchrotron and neutron facilities - Marcus Noack (Lawrence Berkeley National Laboratory)
10:30 Coffee Break
Coffee Break
10:30 - 11:00
Room: Compton 241/245
11:00 Advanced Statistics Techniques for Analyzing Experimental Data and for Accelerator design
Advanced Statistics Techniques for Analyzing Experimental Data and for Accelerator design
11:00 - 11:30
Room: Crow 201
Contributions

11:00 Deep learning techniques in ground-based imaging gamma-ray observatories (virtual) - Daniel Nieto (Madrid University)
11:30 Closing/Remarks
Closing/Remarks
11:30 - 12:00
Room: Crow 201

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