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, May 22, 2023 (8:00 AM) to Friday, May 26, 2023 (1:30 PM)

Monday, May 22, 2023

8:00 AM Registration/Breakfast
Registration/Breakfast
8:00 AM - 9:00 AM
Room: Compton 241/245
9:00 AM Session I
Session I
9:00 AM - 10:45 AM
Room: Whitaker 218
Contributions

9:00 AM Welcome and Intro - Maria Piarulli (Washington University)

9:05 AM Gaussian Process emulation using surmise - Moses Chan (Northwestern) Özge Surer (Miami University)
10:45 AM Coffee Break
Coffee Break
10:45 AM - 11:15 AM
Room: Compton 241/245
11:15 AM Session II
Session II
11:15 AM - 12:45 PM
Contributions

11:15 AM Reduced Basis Methods for emulation and the ROSE software package - Daniel Odell (Ohio) Pablo Giuliani (MSU/FRIB)
12:45 PM Lunch Break
Lunch Break
12:45 PM - 2:15 PM
Room: Compton 241/245
2:15 PM Session III
Session III
2:15 PM - 3:45 PM
Room: Whitaker 218
Contributions

2:15 PM Bayesian Model Mixing using Taweret - Alexandra Semposki (Ohio University) John Yannotty (Ohio State) Matt Pratola (Ohio State)
3:45 PM Coffee Break
Coffee Break
3:45 PM - 4:15 PM
Room: Compton 241/245
4:15 PM Session IV
Session IV
4:15 PM - 5:30 PM
Room: Whitaker 218
Contributions

4:15 PM The Bayesian Mass Explorer, BMEX - Kyle Godbey (MSU/FRIB)

4:55 PM Experimental Design and the BAND software framework - Dick Furnstahl (Ohio State) Witek Nazarewicz (MSU/FRIB)
6:00 PM

6:00 PM - 8:00 PM
Room: Women’s Building, Ann W. Olin
Tuesday, May 23, 2023

8:00 AM Registration/Breakfast
Registration/Breakfast
8:00 AM - 8:45 AM
Room: Crow 201/Compton 241/245

8:45 AM Welcome
Welcome
8:45 AM - 9:00 AM
Room: Crow 201
9:00 AM Statistical methods for optimization, Bayesian inference, and uncertainty quantification
Statistical methods for optimization, Bayesian inference, and uncertainty quantification
9:00 AM - 10:30 AM
Room: Crow 201
Contributions

9:00 AM Recent tools and developments in Bayesian statistics - Yuling Yao (Flatiron Institute)

9:30 AM A statistical exploration of CEMP star classification with s-process models - Andrés Yagüe López (Los Alamos National Lab)

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

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

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

12:00 PM History matching for nuclear ab initio calculations - Christian Forssén (Durham University)
12:30 PM Lunch Break
Lunch Break
12:30 PM - 1:30 PM
Room: Compton 241/245
1:30 PM Statistical methods for optimization, Bayesian inference, and uncertainty quantification
Statistical methods for optimization, Bayesian inference, and uncertainty quantification
1:30 PM - 3:00 PM
Room: Crow 201
Contributions

1:30 PM Bayesian probability updates using sampling/importance resampling: applications in nuclear theory - Weiguang Jiang (Chalmers University)

2:00 PM Hamiltonian Monte Carlo computation in spatial statistics - Debashis Mondal (WashU)

2:30 PM Bayesian model calibration for nuclear decays with the Skyrme finite-amplitude method - Tong Li (LLNL)
3:00 PM Coffee Break
Coffee Break
3:00 PM - 3:30 PM
Room: Compton 241/245
3:30 PM Statistical methods for optimization, Bayesian inference, and uncertainty quantification
Statistical methods for optimization, Bayesian inference, and uncertainty quantification
3:30 PM - 4:30 PM
Room: Crow 201
Contributions

3:30 PM Accounting for material and experimental variability using a random effects Bayesian inferential framework - Denielle Ricciardi (Sandia National Laboratories)

4:00 PM Short talk: Bayesian calibration of viscous anisotropic hydrodynamic simulations of heavy-ion collisions - Dananjaya Liyanage

4:15 PM Short Talk: How Uncertain Am I? Theoretical errors in Bayesian model calibration for EFTs - Jason Bub
4:30 PM

4:30 PM - 5:00 PM
Room: Crow 201
Wednesday, May 24, 2023

8:25 AM Breakfast
Breakfast
8:25 AM - 8:55 AM
Room: Crow 201/Compton 241/245
8:55 AM Symposium in Honor of John Clark: Different Aspects of Machine Learning
Symposium in Honor of John Clark: Different Aspects of Machine Learning
8:55 AM - 10:30 AM
Room: Crow 201
Contributions

8:55 AM Prof. John W. Clark - Henric Krawczynski

9:00 AM John Clark: Physicist at the computational frontier (virtual) - Henrik Bohr

9:45 AM Machine learning for nuclear physics - Witek Nazarewicz (MSU/FRIB)
10:30 AM Coffee Break
Coffee Break
10:30 AM - 11:00 AM
Room: Compton 241/245
11:00 AM Symposium in Honor of John Clark: Different Aspects of Machine Learning
Symposium in Honor of John Clark: Different Aspects of Machine Learning
11:00 AM - 12:15 PM
Room: Crow 201
Contributions

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

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

11:45 AM Machine learning for heavy-ion accelerators (virtual) - Yue Hao (Michigan State University)
12:15 PM Lunch Break
Lunch Break
12:15 PM - 1:15 PM
Room: Compton 241/245
1:15 PM Symposium in Honor of John Clark: Different Aspects of Machine Learning
Symposium in Honor of John Clark: Different Aspects of Machine Learning
1:15 PM - 2:45 PM
Room: Crow 201
Contributions

1:15 PM Nuclear masses learned from a probabilistic neural network - Amy Lovell (Los Alamos National Lab)

1:45 PM Machine learning for the many-body problem - Alessandro Lovato (Argonne National laboratory)

2:15 PM Mapping out the thermodynamic stability of a QCD EOS with a critical point using active learning - Debora Mroczek (University of Illinois)
2:45 PM Coffee Break
Coffee Break
2:45 PM - 3:15 PM
Room: Compton 241/245
3:15 PM Symposium in Honor of John Clark: Different Aspects of Machine Learning
Symposium in Honor of John Clark: Different Aspects of Machine Learning
3:15 PM - 4:30 PM
Room: Crow 201
Contributions

3:15 PM Predicting nuclear masses with product-unit networks (virtual) - Babette Dellen

3:45 PM Machine learning for Deeply Virtual Compton Scattering (virtual) - Manal Almaeen

4:15 PM Short Talk: Deep learning pairing correlations from neural-network quantum states - Jane Kim
4:30 PM

4:30 PM - 5:00 PM
Room: Crow 201

6:00 PM

6:00 PM - 9:00 PM
Room: The Boathouse at Forest Park
Thursday, May 25, 2023

8:30 AM Breakfast
Breakfast
8:30 AM - 9:00 AM
Room: Compton 241/245
9:00 AM Emulators and Resampling Techniques
Emulators and Resampling Techniques
9:00 AM - 10:30 AM
Room: Crow 201
Contributions

9:00 AM Overview of emulators for nuclear physics - Dick Furnstahl

9:30 AM Known Boundary Emulation (virtual) - Ian Vernon

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

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

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

12:00 PM Hamiltonian Monte Carlo & eigenvector continuation for ab initio nuclear physics - Andreas Ekström (Chalmers University of Technology)
12:30 PM Lunch Break
Lunch Break
12:30 PM - 1:30 PM
Room: Compton 241/245
1:30 PM Emulators and Resampling Techniques
Emulators and Resampling Techniques
1:30 PM - 3:00 PM
Room: Crow 201
Contributions

1:30 PM Eigenvector continuation emulators for the ab initio symmetry-adapted framework - Kevin Becker

2:00 PM Bootstrap for multivariate time series and gravitational wave detection - Soumen Lahiri (Washington University)

2:30 PM Data integration using constrained Gaussian process models with applications to nuclear physics - Shuang Zhou (Arizona State University)
3:00 PM Coffee Break
Coffee Break
3:00 PM - 3:30 PM
Room: Compton 241/245
3:30 PM Emulators and Resampling Techniques
Emulators and Resampling Techniques
3:30 PM - 4:15 PM
Room: Crow 201
Contributions

3:30 PM Short Talk: Potential energy surface emulation and impact on fission trajectories - Daniel Lay

3:45 PM Short Talk: Ex fissio ad astra: extending optical models to the fission fragment region - Kyle Beyer

4:00 PM Short Talk: Reduced Basis Methods and Scattering - Daniel Odell
4:15 PM

4:15 PM - 4:45 PM
Room: Crow 201

4:45 PM

4:45 PM - 5:45 PM
Friday, May 26, 2023

8:30 AM Breakfast
Breakfast
8:30 AM - 9:00 AM
Room: Compton 241/245
9:00 AM Advanced Statistics Techniques for Analyzing Experimental Data and for Accelerator design
Advanced Statistics Techniques for Analyzing Experimental Data and for Accelerator design
9:00 AM - 10:30 AM
Room: Crow 201
Contributions

9:00 AM AI/ML+data science tools for detector design at the Electron Ion Collider (virtual) - Cristiano Fanelli (William & Mary)

9:30 AM Excavating insights from sparse data with statistics and machine learning - Kyle Godbey

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

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

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