Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Alexander Politowicz"'
Autor:
Glenn Palmer, Siqi Du, Alexander Politowicz, Joshua Paul Emory, Xiyu Yang, Anupraas Gautam, Grishma Gupta, Zhelong Li, Ryan Jacobs, Dane Morgan
Publikováno v:
npj Computational Materials, Vol 8, Iss 1, Pp 1-9 (2022)
Abstract Obtaining accurate estimates of machine learning model uncertainties on newly predicted data is essential for understanding the accuracy of the model and whether its predictions can be trusted. A common approach to such uncertainty quantific
Externí odkaz:
https://doaj.org/article/c8ff8838611448319aa4e6305809ec41
Autor:
Yu-chen Liu, Henry Wu, Tam Mayeshiba, Benjamin Afflerbach, Ryan Jacobs, Josh Perry, Jerit George, Josh Cordell, Jinyu Xia, Hao Yuan, Aren Lorenson, Haotian Wu, Matthew Parker, Fenil Doshi, Alexander Politowicz, Linda Xiao, Dane Morgan, Peter Wells, Nathan Almirall, Takuya Yamamoto, G. Robert Odette
Publikováno v:
npj Computational Materials, Vol 8, Iss 1, Pp 1-11 (2022)
Abstract Irradiation increases the yield stress and embrittles light water reactor (LWR) pressure vessel steels. In this study, we demonstrate some of the potential benefits and risks of using machine learning models to predict irradiation hardening
Externí odkaz:
https://doaj.org/article/68cdcbbe70b94b6dbae6e0c0e68a3e20
Autor:
Nianzu Ma, Alexander Politowicz, Sahisnu Mazumder, Jiahua Chen, Bing Liu, Eric Robertson, Scott Grigsby
Publikováno v:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::109c0cc46a88e9acfd45a867b9c6c508
https://doi.org/10.18653/v1/2021.emnlp-main.66
https://doi.org/10.18653/v1/2021.emnlp-main.66
Autor:
Xianjia Shao, Dane Morgan, Xiaoyu Sun, Alfred Sunaryo, Mingren Shen, Alexander Politowicz, Qiying Li, Wei-Ting Chen, Nathaniel J. Krakauer, James Wang, Zuoyi Li
Flash points of organic molecules play an important role in preventing flammability hazards and large databases of measured values exist, although millions of compounds remain unmeasured. To rapidly extend existing data to new compounds many research
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::19e699a23c154a6caf551055e7a2cafb
Publikováno v:
Carbon. 132:199-209
Low density aerogels are promising materials for oil absorption, but they typically suffer from low compressibility and elasticity. Herein, three-dimensional (3D) highly compressible, elastic, anisotropic, cellulose/graphene aerogels (CGAs) were prep
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e7e2bcada7a73018ba23baf59a0264bd
https://doi.org/10.1016/j.carbon.2018.02.033
https://doi.org/10.1016/j.carbon.2018.02.033