Randomized Algorithms for Scientific Computing (RASC)
Randomized algorithms have propelled advances in artificial intelligence and represent a foundational research area in advancing AI for Science. Future advancements in DOE Office of Science priority areas such as climate science, astrophysics, fusion, advanced materials, combustion, and quantum comp...
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| Veröffentlicht in: | arXiv.org 2022-03 |
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| creator | Aydin Buluc Kolda, Tamara G Wild, Stefan M Anitescu, Mihai DeGennaro, Anthony Jakeman, John Kamath, Chandrika Ramakrishnan Kannan Lopes, Miles E Martinsson, Per-Gunnar Myers, Kary Nelson, Jelani Restrepo, Juan M Seshadhri, C Vrabie, Draguna Brendt Wohlberg Wright, Stephen J Yang, Chao Zwart, Peter |
| description | Randomized algorithms have propelled advances in artificial intelligence and represent a foundational research area in advancing AI for Science. Future advancements in DOE Office of Science priority areas such as climate science, astrophysics, fusion, advanced materials, combustion, and quantum computing all require randomized algorithms for surmounting challenges of complexity, robustness, and scalability. This report summarizes the outcomes of that workshop, "Randomized Algorithms for Scientific Computing (RASC)," held virtually across four days in December 2020 and January 2021. |
| doi_str_mv | 10.48550/arxiv.2104.11079 |
| format | Article |
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| subjects | Algorithms Artificial intelligence Astrophysics Computer Science - Artificial Intelligence Computer Science - Computational Engineering, Finance, and Science Quantum computing |
| title | Randomized Algorithms for Scientific Computing (RASC) |
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