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06/13/2019
Efficient calibration for high-dimensional computer model output using basis methods
Calibration of expensive computer models with high-dimensional output fi...
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05/03/2019
How are emergent constraints quantifying uncertainty and what do they leave behind?
The use of emergent constraints to quantify uncertainty for key policy r...
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08/28/2018
Quantifying spatio-temporal boundary condition uncertainty for the North American deglaciation
Ice sheet models are used to study the deglaciation of North America at ...
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07/07/2018
State-space modeling of intra-seasonal persistence in daily climate indices: a data-driven approach for seasonal forecasting
Existing methods for diagnosing predictability in climate indices often ...
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03/13/2018
Nonstationary Gaussian Process Emulators with Kernel Mixtures
Weakly stationary Gaussian processes are the principal tool in the stati...
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01/24/2018
Uncertainty quantification for spatio-temporal computer models with calibration-optimal bases
The calibration of complex computer codes using uncertainty quantificati...
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11/11/2017