38 citations · 87 across the 35 of their papers we have counts for
6 papers · 1 filter
Inverse Design of Nonlinear Mechanics of Bio-inspired Materials Through Interface Engineering and Bayesian Optimization
Wei Zhang, Mingjian Tang, Haoxuan Mu +6
In many biological materials such as nacre and bone, the material structure consists of hard grains and soft interfaces, with the interfaces playing a significant role in the mater…
Aggregation Models with Optimal Weights for Distributed Gaussian Processes
Haoyuan Chen, Rui Tuo
Gaussian process (GP) models have received increasing attention in recent years due to their superb prediction accuracy and modeling flexibility. To address the computational burde…
Gaussian Processes Sampling with Sparse Grids under Additive Schwarz Preconditioner
Haoyuan Chen, Rui Tuo
Gaussian processes (GPs) are widely used in non-parametric Bayesian modeling, and play an important role in various statistical and machine learning applications. In a variety task…
Fixed-budget optimal designs for multi-fidelity computer experiments
Gecheng Chen, Rui Tuo
This work focuses on the design of experiments of multi-fidelity computer experiments. We consider the autoregressive Gaussian process model proposed by Kennedy and O'Hagan (2000)…
Asymptotic Theory for Linear Functionals of Kernel Ridge Regression
Rui Tuo, Lu Zou
An asymptotic theory is established for linear functionals of the predictive function given by kernel ridge regression, when the reproducing kernel Hilbert space is equivalent to a…
Beyond State Space Representation: A General Theory for Kernel Packets
Liang Ding, Rui Tuo, Lu Zhou
Gaussian process (GP) regression provides a flexible, nonparametric framework for probabilistic modeling, yet remains computationally demanding in large-scale applications. For one…