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217 !
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Wed, 8/11/2021,
10:00 AM -
11:50 AM
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Virtual
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High-Fidelity Gaussian Process Surrogate Modeling: Deep and Shallow — Invited Papers
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Section on Physical and Engineering Sciences
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Organizer(s): Anindya Bhadra, Purdue University; Robert B Gramacy, Virginia Tech
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Chair(s): Robert B Gramacy, Virginia Tech
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10:05 AM
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Computer Model Emulation and Uncertainty Quantification Using a Deep Gaussian Process
Derek Bingham, Simon Fraser University; Ilya Mandel, School of Physics and Astronomy, Monash University; Daniel Williamson, University of Exeter; Faezeh Yazdi, Simon Fraser University
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10:30 AM
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Active Learning for Deep Gaussian Process Surrogates
Annie Sauer, Virginia Tech
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10:55 AM
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Beyond Matérn: On a Class of Interpretable Confluent Hypergeometric Covariance Functions
Pulong Ma, Duke University / SAMSI; Anindya Bhadra, Purdue University
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11:20 AM
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DeepKriging: Spatially Dependent Deep Neural Networks for Spatial Prediction
Yuxiao Li, King Abdullah University of Science and Technology (KAUST); Ying Sun, King Abdullah University of Science and Technology (KAUST); Brian Reich, North Carolina State University
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11:45 AM
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Floor Discussion
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