Presentations


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About BAND

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.


BAND methodology

See also videos and slides from BAND Camp 2023.

Heterogeneous multi-output Gaussian process for noisy computer models
Moses Chan (Northwestern)
SIAM Annual Meeting 2024, Spokane, Washington
July 11, 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.


BAND physics applications

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.


BAND Camp 2023

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