30 citations · 170 across the 22 of their papers we have counts for
6 papers · 1 filter
Calibration of imperfect geophysical models by multiple satellite interferograms with measurement bias
Mengyang Gu, Kyle Anderson, Erika McPhillips
Model calibration consists of using experimental or field data to estimate the unknown parameters of a mathematical model. The presence of model discrepancy and measurement bias in…
Generalized probabilistic principal component analysis of correlated data
Mengyang Gu, Weining Shen
Principal component analysis (PCA) is a well-established tool in machine learning and data processing. The principal axes in PCA were shown to be equivalent to the maximum marginal…
Nonparametric estimation of utility functions
Mengyang Gu, Debarun Bhattacharjya, Dharmashankar Subramanian
Inferring a decision maker's utility function typically involves an elicitation phase where the decision maker responds to a series of elicitation queries, followed by an estimatio…
A theoretical framework of the scaled Gaussian stochastic process in prediction and calibration
Mengyang Gu, Fangzheng Xie, Long Wang
Model calibration or data inversion is one of fundamental tasks in uncertainty quantification. In this work, we study the theoretical properties of the scaled Gaussian stochastic p…
Jointly Robust Prior for Gaussian Stochastic Process in Emulation, Calibration and Variable Selection
Mengyang Gu
Gaussian stochastic process (GaSP) has been widely used in two fundamental problems in uncertainty quantification, namely the emulation and calibration of mathematical models. Some…
RobustGaSP: Robust Gaussian Stochastic Process Emulation in R
Mengyang Gu, Jesús Palomo, James O. Berger
Gaussian stochastic process emulation is a powerful tool for approximating computationally intensive computer models. However, estimation of parameters in the GaSP emulator is a ch…