Analyzing stochastic computer models: A review with opportunities
Analyzing Stochastic Computer Models: A Review with Opportunities Page 1 Statistical
Science 2022, Vol. 37, No. 1, 64–89 https://doi.org/10.1214/21-STS822 © Institute of …
Science 2022, Vol. 37, No. 1, 64–89 https://doi.org/10.1214/21-STS822 © Institute of …
Simulation experiments: Better data, not just big data
SM Sanchez - … of the Winter Simulation Conference 2014, 2014 - ieeexplore.ieee.org
Data mining tools have been around for several decades, but the term “big data” has only
recently captured widespread attention. Numerous success stories have been promulgated …
recently captured widespread attention. Numerous success stories have been promulgated …
Fully-sequential space-filling design algorithms for computer experiments
Fully-sequential (ie, with design points added one-at-a-time) space-filling designs are useful
for global surrogate modeling of expensive computer experiments when the number of …
for global surrogate modeling of expensive computer experiments when the number of …
Better big data via data farming experiments
SM Sanchez, PJ Sánchez - … and Simulation: Seminal Research from 50 …, 2017 - Springer
The term 'big data'has become intertwined with 'data mining'in the minds of many people.
Modern computing can generate massive amounts of data via simulation studies, but a key …
Modern computing can generate massive amounts of data via simulation studies, but a key …
Collaborative and Distributed Bayesian Optimization via Consensus: Showcasing the Power of Collaboration for Optimal Design
Optimal design is a critical yet challenging task within many applications. This challenge
arises from the need for extensive trial and error, often done through simulations or running …
arises from the need for extensive trial and error, often done through simulations or running …
Batch-sequential design and heteroskedastic surrogate modeling for delta smelt conservation
Batch-sequential design and heteroskedastic surrogate modeling for delta smelt conservation
Page 1 The Annals of Applied Statistics 2022, Vol. 16, No. 2, 816–842 https://doi.org/10.1214/21-AOAS1521 …
Page 1 The Annals of Applied Statistics 2022, Vol. 16, No. 2, 816–842 https://doi.org/10.1214/21-AOAS1521 …
Dispersion‐enhanced sequential batch sampling for adaptive contour estimation
In computer simulation and optimal design, sequential batch sampling offers an appealing
way to iteratively stipulate optimal sampling points based upon existing selections and …
way to iteratively stipulate optimal sampling points based upon existing selections and …
Design for sequential follow-up experiments in computer emulations
X Kong, M Ai, KL Tsui - Technometrics, 2018 - Taylor & Francis
Sequential experiments composed of initial experiments and follow-up experiments are
widely adopted for economical computer emulations. Many kinds of Latin hypercube …
widely adopted for economical computer emulations. Many kinds of Latin hypercube …
Multi-agent Collaborative Bayesian Optimization via Constrained Gaussian Processes
The increase in the computational power of edge devices has opened a new paradigm for
collaborative analytics whereby agents borrow strength from each other to improve their …
collaborative analytics whereby agents borrow strength from each other to improve their …
A sequential maximum projection design framework for computer experiments with inert factors
S Ba, WR Myers, D Wang - Statistica Sinica, 2018 - JSTOR
Many computer experiments involve a large number of input factors, but many of them are
inert and only a subset are important. This paper develops a new sequential design …
inert and only a subset are important. This paper develops a new sequential design …