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The Bayesian Analysis of Nuclear Dynamics Framework
Özge Sürer (Miami)
Talk at 2024 STAR Collaboration Meeting Spring Juniors Day
March 18, 2024
The Bayesian Analysis of Nuclear Dynamics Framework
Özge Sürer (Miami)
Talk at 2022 Fall Meeting of the Division of Nuclear Physics of the American Physical Society
October 29, 2022
The Bayesian Analysis of Nuclear Dynamics CI Framework
Daniel Phillips (Ohio)
Talk at Mid-West Theory Get-together at Argonne National Laboratory
September 30, 2022
Bayesian Model Averaging: applications and perspectives
Witek Nazarewicz (MSU/FRIB)
Talk at INT program “Machine learning for nuclear theory” (INT-22-1)
March 30, 2022
On the Horizon
Pablo Giuliani (MSU/FRIB)
Talk at 2021 ISNET
December 14, 2021
The Bayesian Analysis of Nuclear Dynamics (BAND) CI Framework: Coming Attractions
Daniel Phillips (Ohio)
Talk at 2021 BAND camp
December 13, 2021
The Bayesian Analysis of Nuclear Dynamics (BAND) Framework: An Introduction
Daniel Phillips (Ohio)
Talk at joint BAND-JETSCAPE meeting
March 16, 2021
Jump to talks about BAND or BAND physics applications.
See also videos and slides from BAND Camp 2023.
An active learning performance model for parallel Bayesian calibration of expensive simulations
Stefan Wild (Northwestern/LBNL)
NeurIPS Workshop on Bayesian Decision-making and Uncertainty, Vancouver, Canada
December 14, 2024
Performance analysis of sequential experimental design for calibration in parallel computing environments
Stefan Wild (Northwestern/LBNL)
SIAM Conference on Mathematics for Data Science, Atlanta, Georgia
December 14, 2024
An introduction to Bayesian statistics for nuclear physicists
Daniel Phillips (Ohio)
10th Workshop on Information and Statistics in Nuclear Experiment and Theory, Fudan University, Shanghai, China (remote)
November 11, 2024
Simulation experiment design for calibration via active learning
Özge Sürer (Miami)
INFORMS Annual Meeting 2024, Seattle, WA
October 21, 2024
Heterogeneous multi-output Gaussian process for noisy computer models
Moses Chan (Northwestern)
SIAM Annual Meeting 2024, Spokane, Washington
July 11, 2024
Sequential Bayesian experimental design for calibration of expensive simulation models
Özge Sürer (Miami)
The Design and Analysis of Experiments Conference, Blacksburg, VA
May 15-17, 2024
Fast & accurate emulation using reduced-basis methods
Dick Furnstahl (OSU)
Wayne State University Physics Colloquium
April 4, 2024
Bayesian Model Mixing with applications in Nuclear Physics and Climate
Matt Pratola (Ohio State)
SIAM UQ 2024, Trieste
February 27, 2024
Performance Analysis of Sequential Experimental Design for Calibration of Simulation Models
Özge Sürer (Miami)
Talk at the INFORMS Annual Meeting 2023, Phoenix AZ.
October 15-18, 2023
Simulation Surrogate for Stochastic High-Dimensional Outputs with Heterogeneous Error
Moses Y-H. Chan (Northwestern)
Talk at the INFORMS Annual Meeting 2023, Phoenix AZ.
October 15-18, 2023
Bayesian Model Mixing Of Computer Simulators
John C. Yannotty (OSU)
Talk at the INFORMS Annual Meeting 2023, Phoenix AZ.
October 15-18, 2023
Accelerating Randomized Adaptive Subspace Trust-Region Algorithms
Stefan M. Wild (LBNL, Northwestern)
Talk at the INFORMS Annual Meeting 2023, Phoenix AZ.
October 15-18, 2023
Reduced Basis Methods & Scattering
Daniel Odell (OU)
Talk at the Information and Statistics in Nuclear Experiment and Theory (ISNET-9) conference.
May 25, 2023
Sorry Maria, I forgot to change my title: Dimensionality reduction for accelerating uncertainty quantification
Pablo Giuliani (MSU)
Talk at the Information and Statistics in Nuclear Experiment and Theory (ISNET-9) conference.
May 25, 2023
Overview of emulators for nuclear physics
Dick Furnstahl (OSU)
Talk at the Information and Statistics in Nuclear Experiment and Theory (ISNET-9) conference.
May 25, 2023
Less is more: Dimensionality reduction for accelerating uncertainty quantification
Pablo Giuliani (MSU)
Talk at the Institute of Nuclear & Particle Physics, Ohio University
January 24, 2023
Training and Projecting: A Reduced Basis Method Emulator for Many-Body Physics
Pablo Giuliani (MSU)
Talk at 2022 Fall Meeting of the Division of Nuclear Physics of the American Physical Society
October 28, 2022
Uncertainties here, there, and everywhere: interpolating between small- and large-g expansions using Bayesian Model Mixing
Daniel Phillips (Ohio)
Talk at 2022 Fall Meeting of the Division of Nuclear Physics of the American Physical Society
October 28, 2022
Batch Sequential Calibration of a Computationally Intensive Simulation Model Using Parallel Computing
Özge Sürer (Northwestern)
Talk at 2022 INFORMS Annual Meeting
October 16-19, 2022
Model Mixing with Bayesian Additive Regression Trees
John Yannotty (OSU)
Talk at 2022 INFORMS Annual Meeting
October 16-19, 2022
Applying Variational Inference on High-dimensional Gaussian Processes with Inducing Points
Moses Chan (Northwestern)
Talk at 2022 INFORMS Annual Meeting
October 16-19, 2022
Uncertainties here, there, and everywhere: Bayesian Model Mixing in nuclear physics
Alexandra Semposki (Ohio)
Talk at Mid-West Theory Get-together at Argonne National Laboratory
October 1, 2022
A Sequential Approach to Calibration of a Computationally Intensive Model
Özge Sürer (Northwestern)
Talk at 2022 SIAM Conference on Uncertainty Quantification
April 12-15, 2022
Taking Shortcuts: Accelerating scientific discovery through physics-informed emulators
Pablo Giuliani (MSU/FRIB)
Research discussion at the Facility for Rare Isotope Beams
April 07 2022
Calibration of a Computationally Intensive Model with Parallel Computing Aspects
Özge Sürer (Northwestern)
Talk at 2022 SIAM Conference on Parallel Processing for Scientific Computing
February 23-26, 2022
Calibration Using Emulation of Filtered Simulation Results
Özge Sürer (Northwestern)
Talk at 2021 Winter Simulation Conference
December 15-17, 2021
Transfer Learning Emulation
Dan Liyanage (OSU)
Talk at 2021 ISNET
December 14, 2021
Bayesian Surrogate Constructions for Calibration of Expensive Simulation Model
Moses Chan (Northwestern)
Talk at 2021 INFORMS Annual Meeting
October 24-27, 2021
Calibration Using Emulation of Filtered Simulation Results
Özge Sürer (Northwestern)
Talk at 2021 INFORMS Annual Meeting
October 24-27, 2021
Transfer Learning for Emulation of Hydrodynamic Simulations
Dan Liyanage (OSU)
Talk at 2021 Fall Meeting of the APS DNP
October 13, 2021
Interpolating between small- and large-x expansions using Bayesian Model Mixing
Alexandra Semposki (Ohio University)
Talk at 2021 Fall Meeting of the APS DNP
October 12, 2021
The Ultimate Shortcut
Pablo Giuliani (MSU/FRIB)
Nuclear Seminar at Florida State University
September 10, 2021
Jump to talks about BAND or BAND methodology.
From chiral EFT to perturbative QCD: a Bayesian model mixing approach to dense nuclear matter
Alexandra Semposki (Ohio)
Invited FRIB IRL-NPA workshop talk, Facility for Rare Isotope Beams
October 31, 2024
From chiral EFT to perturbative QCD: a Bayesian model mixing approach to dense nuclear matter
Alexandra Semposki (Ohio)
Invited LANL T-2 (Theoretical Division) seminar, Los Alamos National Laboratory
August 20, 2024
Bridging the gap: a Bayesian model mixing approach to the dense matter equation of state
Alexandra Semposki (Ohio)
Invited UQNP24 workshop talk, Mainz Institute for Theoretical Physics, Germany
June 27, 2024
Knowing What You Don’t Know: Bayesian Uncertainty Quantification of Theoretical Uncertainties in Nuclear Physics
Daniel Phillips (Ohio)
Ångstrom Colloquium, Physics Department, Lund University, Sweden
May 7, 2024
From chiral EFT to perturbative QCD: a Bayesian model mixing approach to symmetric nuclear matter
Alexandra Semposki (Ohio)
Invited FRIB nuclear theory seminar, Facility for Rare Isotope Beams
April 16, 2024
Nuclear forecasting: how effective field theory and uncertainty quantification enable predictive nuclear theory
Daniel Phillips (Ohio)
Lecture in the Department of Physics, Chalmers University of Technology
April 11, 2024
Assessing the progress through quantified nuclear structure theory
Witek Nazarewicz (Michigan State/FRIB)
INTRANS 2024 Workshop, Orsay
January 22, 2024
Mind the gaps: applying Bayesian model mixing to the dense matter equation of state
Alexandra Semposki (Ohio)
Talk at the 6th Joint Meeting of the APS Division of Nuclear Physics and the Physical Society of Japan
November 29, 2023
Mind the gaps: Bayesian model mixing and the dense matter equation of state
Alexandra Semposki (Ohio)
Invited seminar at University of Illinois Urbana-Champaign
November 13, 2023
Acknowledging the existence of a higher power: how ‘discrepancy modeling’ of truncation uncertainties in EFT expansions improves parameter estimation and uncovers underlying physics
Daniel Phillips (Ohio)
Talk at the Institute for Nuclear Theory workshop, “Theoretical Uncertainties to Empower Neutrino Experiments”
October 30-November 3, 2023
Bayesian calibration of viscous anisotropic hydrodynamic simulations of heavy-ion collisions
Ulrich Heinz (OSU)
Talk at the Quark Matter 2023 conference (Houston, TX).
September 06, 2023
Machine learning for nuclear physics
Witek Nazarewicz (MSU)
Talk at the Information and Statistics in Nuclear Experiment and Theory (ISNET-9) conference.
May 23, 2023
Bayesian calibration of viscous anisotropic hydrodynamic simulations of heavy-ion collisions
Dan Liyanage (OSU)
Talk at the Information and Statistics in Nuclear Experiment and Theory (ISNET-9) conference.
May 23, 2023
Sequential Bayesian experimental design for calibration of expensive physics models
Özge Sürer (Miami)
Talk at the Information and Statistics in Nuclear Experiment and Theory (ISNET-9) conference.
May 23, 2023
Bayesian Parameter Estimation with Viscous Anisotropic Hydrodynamic Modeling
Dan Liyanage (OSU)
Talk at 2022 Fall Meeting of the Division of Nuclear Physics of the American Physical Society
October 29, 2022
Emulating the R-Matrix
Daniel Odell (Ohio)
Talk at 2022 Fall Meeting of the Division of Nuclear Physics of the American Physical Society
October 28, 2022
Artificial intelligence and machine learning in nuclear structure theory
Witek Nazarewicz (MSU/FRIB)
Seminar at Fudan University, Shanghai, China
August 3, 2022
Bayesian R-Matrix
Daniel Odell (Ohio University)
Talk at 2021 ISNET
December 14, 2021
Statistically rigorous analyses of light nuclei with chiral interactions
Dick furnstahl (OSU)
Invite talk at Chiral Dynamics 2021 (virtual)
November 15-19, 2021
Artificial intelligence and machine learning in nuclear structure theory
Witold Nazarewicz (MSU/FRIB)
IAEA Virtual Meeting on Artificial Intelligence for Nuclear Technology and Applications, Vienna
October 25-29, 2021
Improved Uncertainties Estimates with R-Matrix Theory
Daniel Odell (Ohio University)
Virtual Seminar at Tongji University
September 16, 2021
Improved Uncertainties Estimates with R-Matrix Theory
Daniel Odell (Ohio University)
Virtual Seminar at the Joint Institute of Nuclear Astrophysics, University of Notre Dame
September 6, 2021
Transfer Learning Emulation of Relativistic Heavy Ion Simulations
Dan Liyanage (OSU)
Virtual Seminar for University of Tennessee Heavy Ion Group
August 10, 2021
Bayesian Parameter Estimation For Relativistic Heavy Ion Collisions
Dan Liyanage (OSU)
Workshop at 2021 JETSCAPE Summer School
July 29, 2021
Bayesian Model Mixing: Nuclear Physics Applications
Witek Nazarewicz (MSU/FRIB)
Invited talk at the ECT* workshop on Advances in Many Body Theories: from First Principles Methods to Quantum Computing and Machine Learning, Trento, Italy
November 2, 2020
Jump to talks about BAND or BAND methodology.
Pre-BAND-camp YouTube video introducing Bayesian methods (60 min.)
Pablo Giuliani (MSU) and Federi Viens (MSU)
BAND Camp at the Information and Statistics in Nuclear Experiment and Theory (ISNET-9) conference.
May 15, 2023
The Bayesian Analysis of Nuclear Dynamics Framework
[video]
Özge Sürer (Miami) and Moses Chan (Northwestern)
BAND Camp at the Information and Statistics in Nuclear Experiment and Theory (ISNET-9) conference.
May 22, 2023
ROSE: Theory and implementation
[video]
Daniel Odell (OU) and Pablo Giuliani (MSU)
BAND Camp at the Information and Statistics in Nuclear Experiment and Theory (ISNET-9) conference.
May 22, 2023
Bayesian Model Mixing: Theory
[video]
Matt Pratola (OSU)
BAND Camp at the Information and Statistics in Nuclear Experiment and Theory (ISNET-9) conference.
May 22, 2023
Bayesian Model Mixing using Taweret
[video]
Alexandra Semposki (OU) and John Yannotty (OSU)
BAND Camp at the Information and Statistics in Nuclear Experiment and Theory (ISNET-9) conference.
May 22, 2023
The Bayesian Mass Explorer, BMEX
[video]
Kyle Godbey (MSU) and Witek Nazarewicz (MSU)
BAND Camp at the Information and Statistics in Nuclear Experiment and Theory (ISNET-9) conference.
May 22, 2023
Experimental Design and the BAND software framework
[video]
Dick Furnstahl (OSU)
BAND Camp at the Information and Statistics in Nuclear Experiment and Theory (ISNET-9) conference.
May 22, 2023