activity
20172021
most citedRobust Gaussian Stochastic Process Emulation

4 citations · 4 across the 2 of their papers we have counts for

collaborators

7 papers

cs.NI2021

Characterizing Performance Inequity Across U.S. Ookla Speedtest Users

Udit Paul, Jiamo Liu, Vivek Adarsh +3

The Internet has become indispensable to daily activities, such as work, education and health care. Many of these activities require Internet access data rates that support real-ti…

cs.CE2020

Emulating the First Principles of Matter: A Probabilistic Roadmap

Jianzhong Wu, Mengyang Gu

This chapter provides a tutorial overview of first principles methods to describe the properties of matter at the ground state or equilibrium. It begins with a brief introduction t…

stat.ME2018

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…

stat.AP2018

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…

math.ST2018

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…

stat.ME2018

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…