AICEApr 19, 2021

Randomized Algorithms for Scientific Computing (RASC)

arXiv:2104.11079v312 citations
Originality Synthesis-oriented
AI Analysis

It addresses the need for randomized algorithms to advance AI in science for domains such as climate and materials, but is incremental as it only summarizes workshop outcomes.

This report summarizes a workshop on randomized algorithms for scientific computing, highlighting their role in addressing complexity, robustness, and scalability challenges in priority areas like climate science and quantum computing.

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.

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The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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