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Showing 1 to 20 of 33 for “"computer experiments"”.
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Validating Gaussian Process Models in Computer Experiments
… about a mathematical model implemented in a computer program known as a simulator. By ``simulator discrepancy'', we mean the difference between a simulator's output and the corresponding physical process. We present a set of diagnostics to validate and assess the adequacy of Gaussian process …
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Scalable Surrogates for Counts and Computer Experiments
… hypotheses about the physical processes, and computer simulations under those models, that are in play at the boundary of our solar system. Providing estimates and associated uncertainty quantification (UQ) of the rate at which ENAs are generated is vital to theory development and validation. …
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Deep Gaussian Process Surrogates for Computer Experiments
… for fast predictions, but applications to computer surrogate modeling - with an eye towards downstream tasks like Bayesian optimization and reliability analysis - demand broader uncertainty quantification (UQ). I prioritize UQ through full posterior integration in a Bayesian scheme, hinging …
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Contributions to quality improvement methodologies and computer experiments
… problem areas in modern quality improvement and computer experiments, i.e., selective assembly, robust design with computer experiments, multivariate quality control, model selection for split plot experiments, and construction of minimax designs. Selective assembly has traditionally been used to …
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Computer experiments with cohort fertility in birth projections.
Massachusetts Institute of Technology. Dept. of City and Regional Planning. Thesis. 1966. M.C.P.
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Transport coefficients from computer experiments: A stochastic Ising model
Submitted by William Weathers (weathrs2@illinois.edu) on 2012-04-11T19:57:56Z No. of bitstreams: 1 1971_sadiq.pdf: 4264941 bytes, checksum: 791b46b8f2b21028fb8864d92f010ae5 (MD5)
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Advancements on the Interface of Computer Experiments and Survival Analysis
Design and analysis of computer experiments is an area focusing on efficient data collection (e.g., space-filling designs), surrogate modeling (e.g., Gaussian process models), and uncertainty quantification. Survival analysis focuses on modeling the period of time until a certain event happens. …
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Modelling of Dynamic Computer Experiments with Both Qualitative and Quantitative Variables
Computer experiments are utilized as a popular tool of studying the relationship between responses and the factors that affect them. They are widely used in scientific researches and applications. Dynamic computer experiments refer to computer experiments with time-series responses. Different …
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Some practical issues in the design and analysis of computer experiments
Deterministic computer simulations of physical experiments are now common techniques in science and engineering. Often, physical experiments are too time consuming, expensive or impossible to conduct. Complex computer models or codes, rather than physical experiments lead to the study of computer …
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Design, estimation, and prediction of computer experiments with applications to spatial data
As computer experiments are widely used in engineering and various other fields of science and technology, stochastic modeling and statistical analysis have been introduced to handle their outputs. Since in certain computer experiments or physical phenomena, measurement error should not be …
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Sequential learning, large-scale calibration, and uncertainty quantification
With remarkable advances in computing power, computer experiments continue to expand the boundaries and drive down the cost of various scientific discoveries. New challenges keep arising from designing, analyzing, modeling, calibrating, optimizing, and predicting in computer experiments. This …
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Gradient-Based Sensitivity Analysis with Kernels
Emulation of computer experiments via surrogate models can be difficult when the number of input parameters determining the simulation grows any greater than a few dozen. In this dissertation, we explore dimension reduction in the context of computer experiments. The active subspace method is a …
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Adapting Response Surface Methods for the Optimization of Black-Box Systems
… partial differential equations. As a result, the computer codes may take a considerable amount of time to complete a single evaluation. A time tested method of analysis for such models is Monte Carlo simulation. These simulations, however, often require many model evaluations, making this approach …
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Computer Experimental Design for Gaussian Process Surrogates
With a rapid development of computing power, computer experiments have gained popularity in various scientific fields, like cosmology, ecology and engineering. However, some computer experiments for complex processes are still computationally demanding. A surrogate model or emulator, is often …
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Significance-linked connected component analysis+ for wavelet image coding
… for the adaptive arithmetic coding. Extensive computer experiments on both natural and texture images show convincingly that the proposed SLCCA+ outperforms SLCCA. For example, for the Lena image, at 0.1 bit/pixel, SLCCA+ outperforms SLCCA by 0.1 dB in PSNR. This outstanding performance is …
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Tuning complex computer codes to data and optimal designs
"Modern scientific researchers often use complex computer simulation codes for theoretical investigations. We model the response of computer simulation code as the realization of a stochastic process. This approach, design and analysis of computer experiments (DACE), provides a statistical basis …
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Statistical Physics of Semidilute Polymer Systems (And); Soft Billiard Systems
… semiquantitative agreement with both real and computer experiments for the static and dynamical properties of polymers in dilute solution. However, polymer theory in the semidilute regime is less sound. We first review RG results on statics, using the so-called direct method and employing the …
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Some Advances in Local Approximate Gaussian Processes
… as an indispensable statistical tool in computer experiments. Due to its computational complexity and storage demand, its application in real-world problems, especially in "big data" settings, is quite limited. Among many strategies to tailor GP to such settings, Gramacy and Apley (2015) …
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