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309 * Wed, 8/5/2020, 10:00 AM - 11:50 AM Virtual
Interface Between Machine Learning and Uncertainty Quantification — Topic Contributed Papers
Uncertainty Quantification in Complex Systems Interest Group, Section on Physical and Engineering Sciences, Section on Statistical Learning and Data Science, Quality and Productivity Section
Organizer(s): Ana Kupresanin, Lawrence Livermore National Laboratory
Chair(s): Kathleen Schmidt, Lawrence Livermore National Laboratory
10:05 AM On-Site Surrogates for Large-Scale Calibration
Jiangeng Huang, University of California Santa Cruz; Robert Gramacy, Virginia Tech
10:25 AM Calibrating Uncertainties in Deep Learning
Bhavya Kailkhura, Lawrence Livermore National Laboratory; Jize Zhang, Lawrence Livermore National Lab
10:45 AM Physics-Informed Machine Learning for Uncertainty Quantification in Land Models
Khachik Sargsyan, Sandia National Laboratories; Cosmin Safta, Sandia National Laboratories; Vishagan Ratnaswamy, Sandia National Laboratories
11:05 AM Quantifying Model Transfer Uncertainties Using Post Hoc Explainability in Deep Learning Models
Evangelina Brayfindley, Pacific Northwest National Laboratory; Thomas Grimes, Pacific Northwest National Lab
11:25 AM Floor Discussion