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pro vyhledávání: '"Eric Phipps"'
Publikováno v:
ACM Transactions on Mathematical Software. 48:1-29
Automatic differentiation (AD) is a well-known technique for evaluating analytic derivatives of calculations implemented on a computer, with numerous software tools available for incorporating AD technology into complex applications. However, a growi
Autor:
Cannada Lewis, Eric Phipps
Publikováno v:
2021 IEEE High Performance Extreme Computing Conference (HPEC).
Publikováno v:
Proposed for presentation at the SIAM Conference on Applied Linear Algebra held May 17-21, 2021 in Virtual, Virtual, Virtual..
Publikováno v:
Proposed for presentation at the 2021 SIAM Conference on Computational Science and Engineering held March 1-5, 2021..
Publikováno v:
Proposed for presentation at the 14th World Congress on Computational Mechanics (Virtual meeting) held January 11-15, 2021..
Autor:
Sarah L. Kieweg, Jaideep Ray, V. G. Weirs, Brian Carnes, Derek Dinzl, Brian Freno, Micah Howard, Eric Phipps, William Rider, Thomas Smith
Publikováno v:
AIAA Scitech 2019 Forum.
The proceedings represent the state of knowledge in the area of algorithmic differentiation (AD). The 31 contributed papers presented at the AD2012 conference cover the application of AD to many areas in science and engineering as well as aspects of
Publikováno v:
Lecture Notes in Computational Science and Engineering ISBN: 9783642300226
Recent Advances in Algorithmic Differentiation
Recent Advances in Algorithmic Differentiation
The proceedings represent the state of knowledge in the area of algorithmic differentiation (AD). The 31 contributed papers presented at the AD2012 conference cover the application of AD to many areas in science and engineering as well as aspects of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ebb636ebe685830bcd656ca0b4afe22f
https://doi.org/10.1007/978-3-642-30023-3
https://doi.org/10.1007/978-3-642-30023-3