Additive Multi-Index Gaussian process modeling, with application to multi-physics surrogate modeling of the quark-gluon plasma
The Quark-Gluon Plasma (QGP) is a unique phase of nuclear matter, theorized to have filled
the Universe shortly after the Big Bang. A critical challenge in studying the QGP is that, to …
the Universe shortly after the Big Bang. A critical challenge in studying the QGP is that, to …
Computer model calibration with time series data using deep learning and quantile regression
Computer models play a key role in many scientific and engineering problems. One major
source of uncertainty in computer model experiments is input parameter uncertainty …
source of uncertainty in computer model experiments is input parameter uncertainty …
Adaptive-region sequential design with quantitative and qualitative factors in application to HPC configuration
Motivated by the need of finding optimal configuration in the high-performance computing
(HPC) system, this work proposes an adaptive-region sequential design (ARSD) for …
(HPC) system, this work proposes an adaptive-region sequential design (ARSD) for …
Calibration for computer experiments with binary responses and application to cell adhesion study
Calibration refers to the estimation of unknown parameters which are present in computer
experiments but not available in physical experiments. An accurate estimation of these …
experiments but not available in physical experiments. An accurate estimation of these …
Optimize to generalize in Gaussian processes: An alternative objective based on the Rényi divergence
X Yue, R Al Kontar - IISE Transactions, 2024 - Taylor & Francis
We introduce an alternative closed-form objective function α-ELBO for improved parameter
estimation in the Gaussian process (GP) based on the Rényi α-divergence. We use a …
estimation in the Gaussian process (GP) based on the Rényi α-divergence. We use a …
Fast L2 Calibration for Inexact Highway Traffic Flow Systems
Transportation systems need more accurate predictions to further optimize traffic network
design with the development and application of autonomous driving technology. In this …
design with the development and application of autonomous driving technology. In this …
Analysis of multivariate non-gaussian functional data: a semiparametric latent process approach
J Jiang, H Lin, Q Zhong, Y Li - Journal of Multivariate Analysis, 2022 - Elsevier
Commonly assumed for multivariate functional regression models are normality and
structural dependence, which, however, may not hold in practice. To relax these restrictions …
structural dependence, which, however, may not hold in practice. To relax these restrictions …
Statistical Inference on Large-scale and Complex Data via Gaussian Process
M Li - 2023 - deepblue.lib.umich.edu
Recent technological advancements have generated vast amounts of complex data in
various fields, including biomedical sciences such as neuroimages, electronic health …
various fields, including biomedical sciences such as neuroimages, electronic health …
Ice model calibration using semicontinuous spatial data
Ice model calibration using semicontinuous spatial data Page 1 The Annals of Applied
Statistics 2022, Vol. 16, No. 3, 1937–1961 https://doi.org/10.1214/21-AOAS1577 © Institute of …
Statistics 2022, Vol. 16, No. 3, 1937–1961 https://doi.org/10.1214/21-AOAS1577 © Institute of …
Renewal model for dependent binary sequences
M Zamparo - Journal of Statistical Physics, 2022 - Springer
We suggest to construct infinite stochastic binary sequences by associating one of the two
symbols of the sequence with the renewal times of an underlying renewal process. Focusing …
symbols of the sequence with the renewal times of an underlying renewal process. Focusing …