Zobrazeno 1 - 10
of 318
pro vyhledávání: '"Apley, Daniel W."'
Simulation-Free Determination of Microstructure Representative Volume Element Size via Fisher Scores
Publikováno v:
APL Mach. Learn. 2(2): 026101 (2024)
A representative volume element (RVE) is a reasonably small unit of microstructure that can be simulated to obtain the same effective properties as the entire microstructure sample. Finite element (FE) simulation of RVEs, as opposed to much larger sa
Externí odkaz:
http://arxiv.org/abs/2404.15207
Autor:
Zhang, Shengtong, Apley, Daniel W.
In many scientific research fields, understanding and visualizing a black-box function in terms of the effects of all the input variables is of great importance. Existing visualization tools do not allow one to visualize the effects of all the input
Externí odkaz:
http://arxiv.org/abs/2303.03393
Real engineering and scientific applications often involve one or more qualitative inputs. Standard Gaussian processes (GPs), however, cannot directly accommodate qualitative inputs. The recently introduced latent variable Gaussian process (LVGP) ove
Externí odkaz:
http://arxiv.org/abs/2211.02218
Publikováno v:
Scientific Reports 12, 19760 (2022)
Data-driven design shows the promise of accelerating materials discovery but is challenging due to the prohibitive cost of searching the vast design space of chemistry, structure, and synthesis methods. Bayesian Optimization (BO) employs uncertainty-
Externí odkaz:
http://arxiv.org/abs/2207.04994
Subsampling from a large data set is useful in many supervised learning contexts to provide a global view of the data based on only a fraction of the observations. Diverse (or space-filling) subsampling is an appealing subsampling approach when no pr
Externí odkaz:
http://arxiv.org/abs/2206.10812
Microstructures are critical to the physical properties of materials. Stochastic microstructures are commonly observed in many kinds of materials and traditional descriptor-based image analysis of them can be challenging. In this paper, we introduce
Externí odkaz:
http://arxiv.org/abs/2012.11135
Supervised learning models are one of the most fundamental classes of models. Viewing supervised learning from a probabilistic perspective, the set of training data to which the model is fitted is usually assumed to follow a stationary distribution.
Externí odkaz:
http://arxiv.org/abs/2012.06916
Autor:
Georgescu, Alexandru B., Ren, Peiwen, Toland, Aubrey R., Zhang, Shengtong, Miller, Kyle D., Apley, Daniel W., Olivetti, Elsa A., Wagner, Nicholas, Rondinelli, James M.
Publikováno v:
Chem. Mater. 33, 14, 5591-5605 (2021)
Metal-insulator transition (MIT) compounds are materials that may exhibit insulating or metallic behavior, depending on the physical conditions, and are of immense fundamental interest owing to their potential applications in emerging microelectronic
Externí odkaz:
http://arxiv.org/abs/2010.13306
Autor:
Bui, Anh Tuan1 (AUTHOR), Apley, Daniel W.2 (AUTHOR) apley@northwestern.edu
Publikováno v:
International Journal of Production Research. Aug2022, Vol. 60 Issue 16, p5071-5086. 16p.
Computer simulations often involve both qualitative and numerical inputs. Existing Gaussian process (GP) methods for handling this mainly assume a different response surface for each combination of levels of the qualitative factors and relate them vi
Externí odkaz:
http://arxiv.org/abs/1806.07504