Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Jueyi Liu"'
Autor:
Haitao D. Deng, Hongbo Zhao, Norman Jin, Lauren Hughes, Benjamin H. Savitzky, Colin Ophus, Dimitrios Fraggedakis, András Borbély, Young-Sang Yu, Eder G. Lomeli, Rui Yan, Jueyi Liu, David A. Shapiro, Wei Cai, Martin Z. Bazant, Andrew M. Minor, William C. Chueh
Publikováno v:
Nature Materials. 21:547-554
Constitutive laws underlie most physical processes in nature. However, learning such equations in heterogeneous solids (e.g., due to phase separation) is challenging. One such relationship is between composition and eigenstrain, which governs the che
Publikováno v:
Artificial Intelligence for the Earth Systems. 1
Resampling methods such as cross validation or bootstrap are often employed to estimate the uncertainty in a loss function due to sampling variability, usually for the purpose of model selection. In models that require nonlinear optimization, however
Autor:
Haitao D, Deng, Hongbo, Zhao, Norman, Jin, Lauren, Hughes, Benjamin H, Savitzky, Colin, Ophus, Dimitrios, Fraggedakis, András, Borbély, Young-Sang, Yu, Eder G, Lomeli, Rui, Yan, Jueyi, Liu, David A, Shapiro, Wei, Cai, Martin Z, Bazant, Andrew M, Minor, William C, Chueh
Publikováno v:
Nature materials. 21(5)
Constitutive laws underlie most physical processes in nature. However, learning such equations in heterogeneous solids (for example, due to phase separation) is challenging. One such relationship is between composition and eigenstrain, which governs
Publikováno v:
Studies in Computational Intelligence ISBN: 9783030653507
COMPLEX NETWORKS (2)
COMPLEX NETWORKS (2)
This study evaluates (1) the properties of a hierarchical network of personnel flow in a large and multilayered Chinese bureaucracy, in light of selected classical network models, and (2) the robustness of the hierarchical network with regard to the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::15971bd0b7a515c3c468745017e70ddc
https://doi.org/10.1007/978-3-030-65351-4_38
https://doi.org/10.1007/978-3-030-65351-4_38