Snowmass 2021计算前沿CompF03专题小组报告：机器学习
Snowmass 2021 Computational Frontier CompF03 Topical Group Report: Machine Learning
摘要：
机器学习（ML）与高能物理（HEP）的快速发展为我们的社区带来了机遇和挑战。除了将标准的机器学习工具应用于HEP问题之外，这两个领域的一代人才正在开发真正新的和潜在的革命性方法。迫切需要支持推动这些发展的跨学科社区的需求，包括资助这两个领域交叉的专门研究，投资于大学的高性能计算并制定分配政策以支持这项工作，开发社区工具和标准，并为被高能物理机器学习的智力活力所吸引的年轻研究人员提供教育和职业道路。
英文摘要：
The rapidly-developing intersection of machine learning (ML) with high-energy physics (HEP) presents both opportunities and challenges to our community. Far beyond applications of standard ML tools to HEP problems, genuinely new and potentially revolutionary approaches are being developed by a generation of talent literate in both fields. There is an urgent need to support the needs of the interdisciplinary community driving these developments, including funding dedicated research at the intersection of the two fields, investing in high-performance computing at universities and tailoring allocation policies to support this work, developing of community tools and standards, and providing education and career paths for young researchers attracted by the intellectual vitality of machine learning for high energy physics.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
