Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Cristina Garcia-Cardona"'
Publikováno v:
Physical Review Accelerators and Beams, Vol 27, Iss 2, p 024601 (2024)
In this work, we develop a machine learning (ML) model with aleatoric uncertainty for the low energy beam transport (LEBT) region of the LANSCE linear accelerator in which we model the transport of a space-charge-dominated 750 keV proton beam through
Externí odkaz:
https://doaj.org/article/6dada45a51a547f696fe9ea528ba714c
Autor:
Fangfang Xia, Maulik Shukla, Thomas Brettin, Cristina Garcia-Cardona, Judith Cohn, Jonathan E. Allen, Sergei Maslov, Susan L. Holbeck, James H. Doroshow, Yvonne A. Evrard, Eric A. Stahlberg, Rick L. Stevens
Publikováno v:
BMC Bioinformatics, Vol 19, Iss S18, Pp 71-79 (2018)
Abstract Background The National Cancer Institute drug pair screening effort against 60 well-characterized human tumor cell lines (NCI-60) presents an unprecedented resource for modeling combinational drug activity. Results We present a computational
Externí odkaz:
https://doaj.org/article/fd72bada8c0f46febf9520c3cdac029a
Publikováno v:
Artificial Intelligence for Science ISBN: 9789811265662
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::81d2226a3b566315c5b7ff9ab7922839
https://doi.org/10.1142/9789811265679_0030
https://doi.org/10.1142/9789811265679_0030
Autor:
Shinjae Yoo, Logan Ward, Nikoli Dryden, Ramakrishnan Kannan, Rajeev Thakur, Bert Debusschere, Ganesh Sivaraman, Sutanay Choudhury, Zhengchun Liu, Neeraj Kumar, Peter Nugent, Francis J. Alexander, Sudip K. Seal, Shantenu Jha, James A. Ang, David Pugmire, Li Tan, Ian Foster, Yunzhi Huang, Paul M. Welch, Cristina Garcia Cardona, Sivasankaran Rajamanickam, Thomas Proffen, Ai Kagawa, Malachi Schram, Byung-Jun Yoon, Jamaludin Mohd-Yusof, Erin McCarthy, Tiernan Casey, Sotiris S. Xantheas, Vinay Ramakrishniah, Jan Balewski, Sayan Ghosh, Brian Van Essen, Michael M. Wolf, Christine Sweeney, J. Austin Ellis, Peter Harrington, Jong Choi, Yosuke Oyama, Naoya Maruyama, Satoshi Matsuoka, Jenna A. Bilbrey, Kevin G. Yager, Anthony M. DeGennaro, Travis Johnston, Ryan Chard
Publikováno v:
The International Journal of High Performance Computing Applications. 35:598-616
Rapid growth in data, computational methods, and computing power is driving a remarkable revolution in what variously is termed machine learning (ML), statistical learning, computational learning, and artificial intelligence. In addition to highly vi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::44a49db17ac8125ad46733a17d870250
https://doi.org/10.1177/10943420211029302
https://doi.org/10.1177/10943420211029302
Autor:
John A Mitchell, Fadi Abdeljawad, Corbett Battaile, Cristina Garcia-Cardona, Elizabeth A Holm, Eric R Homer, Jon Madison, Theron M Rodgers, Aidan P Thompson, Veena Tikare, Ed Webb, Steven J Plimpton
Publikováno v:
Modelling and Simulation in Materials Science and Engineering. 31:055001
SPPARKS is an open-source parallel simulation code for developing and running various kinds of on-lattice Monte Carlo models at the atomic or meso scales. It can be used to study the properties of solid-state materials as well as model their dynamic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6b22d68f48e1635f3d00ac9a35237469
https://doi.org/10.1088/1361-651x/accc4b
https://doi.org/10.1088/1361-651x/accc4b
Publikováno v:
Knowledge-Guided Machine Learning ISBN: 9781003143376
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::043443ef801fa92153a0622001a4be96
https://doi.org/10.1201/9781003143376-12
https://doi.org/10.1201/9781003143376-12
Autor:
Thilo Balke, Fernando Davis, Cristina Garcia-Cardona, Soumendu Majee, Michael McCann, Luke Pfister, Brendt Wohlberg
Publikováno v:
Journal of Open Source Software. 7:4722
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ce5f18abf1cab9cb5162e2fb807ee218
https://doi.org/10.21105/joss.04722
https://doi.org/10.21105/joss.04722
Publikováno v:
4th International Conference on Uncertainty Quantification in Computational Sciences and Engineering.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fdcea6eadb53f46e5c55d99c913c0dce
https://doi.org/10.7712/120221.8045.19145
https://doi.org/10.7712/120221.8045.19145
Autor:
Pinyi Lu, Rick Stevens, Eric Stahlberg, Thomas Brettin, Maulik Shukla, Jason D. Gans, Alexander Partin, Justin M. Wozniak, Austin Clyde, Stewart He, Jonathan E. Allen, Hyunseung Yoo, Fangfang Xia, George Zaki, Prasanna Balaprakash, Yitan Zhu, Cristina Garcia-Cardona, Ya Ju Fan, Xiaotian Duan, Yvonne A. Evrard, Sergei Maslov, James H. Doroshow, Veronika Dubinkina, Judith D. Cohn
Publikováno v:
Briefings in Bioinformatics
To enable personalized cancer treatment, machine learning models have been developed to predict drug response as a function of tumor and drug features. However, most algorithm development efforts have relied on cross validation within a single study
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::898ad84a11ff7d5a7662b49a33d97557