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CC = Walter E. Washington Convention Center M = Marriott Marquis Washington, DC
* = applied session ! = JSM meeting theme
Activity Details
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403 * !
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Wed, 8/10/2022,
10:30 AM -
12:20 PM
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CC-151A
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Research Advances at the Interface of Uncertainty Quantification and Machine Learning for High-Consequence Problems — Invited Papers
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Section on Statistics in Defense and National Security, Section on Statistical Learning and Data Science, IEEE Computer Society
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Organizer(s): Ahmad Rushdi, Stanford University
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Chair(s): Erin Acquesta, Sandia National Laboratories
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10:35 AM
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Variational Inference with NoFAS: Normalizing Flow with Adaptive Surrogate for Computationally Expensive Models
Yu Wang, Notre Dame University; Daniele Schiavazzi, University of Notre Dame; Fang Liu, Univerisity of Notre Dame
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10:55 AM
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Assessing the Quality of Uncertainty Estimates in Deep Learning
Jason Adams, Sandia National Laboratories
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11:15 AM
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Extreme Learning Machines for Variance-Based Global Sensitivity Analysis
John Darges, North Carolina State University; Alen Alexanderian, North Carolina State University; Pierre Gremaud, North Carolina State University
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11:35 AM
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Efficient Variational Approach to Sparse BNN for Model Compression
Diptarka Saha, University of Illinois, Urbana-Champaign; Feng Liang, University of Illinois, Urbana-Champaign ; Zihe Liu, University of Illinois, Urbana-Champaign
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11:55 AM
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Discussant: Daniel Ries, Sandia National Labs
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12:15 AM
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Floor Discussion
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Video Available to all JSM Registered Attendees. Please login to view.
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