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217 ! Wed, 8/11/2021, 10:00 AM - 11:50 AM Virtual
High-Fidelity Gaussian Process Surrogate Modeling: Deep and Shallow — Invited Papers
Section on Physical and Engineering Sciences
Organizer(s): Anindya Bhadra, Purdue University; Robert B Gramacy, Virginia Tech
Chair(s): Robert B Gramacy, Virginia Tech
10:05 AM 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
10:30 AM Active Learning for Deep Gaussian Process Surrogates
Annie Sauer, Virginia Tech
10:55 AM Beyond Matérn: On a Class of Interpretable Confluent Hypergeometric Covariance Functions
Pulong Ma, Duke University / SAMSI; Anindya Bhadra, Purdue University
11:20 AM 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
11:45 AM Floor Discussion