14-17 December 2020
America/New_York timezone


Bayesian Analysis of Nuclear Dynamics (BAND)


Monday, December 14, 2020
10.15 AM-5 PM

In association with the ISNET v8 Workshop, the BAND Collaboration is sponsoring a one-day series of on-line pedagogical lectures aimed at providing a foundation for nuclear physicists in modern Bayesian statistical methodologies. The program consists of three extended lectures, including discussion.



Michael Grosskopf
Computer, Computational, and Statistical Sciences Division,
Los Alamos National Laboratory
"Bayesian Basics"

Simon Mak
Department of Statistical Science, Duke University
"Applications of Model Emulators for Parameter Estimation"

Matthew Pratola
Department of Statistics, The Ohio State University
"Model Mixing and Averaging"



Interested attendees should register through the ISNET registration page. There are no fees for attendance.

The BAND Collaboration was formed in 2020 and is funded by the National Science Foundation's Office of Advanced Cyber-Infrastructure. BAND's goals are to facilitate the implementation of advanced statistical tools for analyzing both models and data in nuclear science. There is a special focus on accounting for multiple models, both for making predictions and for constraining models and their parameters.

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