Sequential learning, large-scale calibration, and uncertainty quantification
With remarkable advances in computing power, computer experiments continue to expand the boundaries and drive down the cost of various scientific discoveries. New challenges keep arising from designing, analyzing, modeling, calibrating, optimizing, and predicting in computer experiments. This disser...
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Virginia Tech
2019
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| Online Access: | http://hdl.handle.net/10919/91935 |