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Uncertainty quantification and estimation in differential dynamic microscopy
Differential dynamic microscopy (DDM) is a form of video image analysis ...
05/03/2021 ∙ by Mengyang Gu, et al. ∙
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Gaussian orthogonal latent factor processes for large incomplete matrices of correlated data
We introduce the Gaussian orthogonal latent factor processes for modelin...
11/21/2020 ∙ by Mengyang Gu, et al. ∙
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Emulating the First Principles of Matter: A Probabilistic Roadmap
This chapter provides a tutorial overview of first principles methods to...
09/30/2020 ∙ by Jianzhong Wu, et al. ∙
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Calibration of imperfect mathematical models by multiple sources of data with measurement bias
Model calibration involves using experimental or field data to estimate ...
10/27/2018 ∙ by Mengyang Gu, et al. ∙
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Generalized probabilistic principal component analysis of correlated data
Principal component analysis (PCA) is a well-established tool in machine...
08/31/2018 ∙ by Mengyang Gu, et al. ∙
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Nonparametric estimation of utility functions
Inferring a decision maker's utility function typically involves an elic...
07/27/2018 ∙ by Mengyang Gu, et al. ∙
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A theoretical framework of the scaled Gaussian stochastic process in prediction and calibration
The Gaussian stochastic process (GaSP) is a useful technique for predict...
07/10/2018 ∙ by Mengyang Gu, et al. ∙
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Jointly Robust Prior for Gaussian Stochastic Process in Emulation, Calibration and Variable Selection
Gaussian stochastic process (GaSP) has been widely used in two fundament...
04/25/2018 ∙ by Mengyang Gu, et al. ∙
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RobustGaSP: Robust Gaussian Stochastic Process Emulation in R
Gaussian stochastic process (GaSP) emulation is a powerful tool for appr...
01/05/2018 ∙ by Mengyang Gu, et al. ∙
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Nonseparable Gaussian Stochastic Process: A Unified View and Computational Strategy
Gaussian stochastic process (GaSP) has been widely used as a prior over ...
11/30/2017 ∙ by Mengyang Gu, et al. ∙
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