论文标题
雪人质量2021计算前沿Compf03主题组报告：机器学习
Snowmass 2021 Computational Frontier CompF03 Topical Group Report: Machine Learning
论文作者
论文摘要
机器学习（ML）与高能量物理（HEP）的快速发展的交集给我们的社区带来了机会和挑战。远远超出了标准ML工具在HEP问题上的应用，这两个领域的一代人才素养正在开发真正的新的和潜在的革命性方法。迫切需要支持跨学科社区推动这些发展的需求，包括在这两个领域的交汇处为专门的研究提供资金，投资大学的高性能计算，并为支持这项工作提供了分配政策，以支持这项工作，开发社区工具和标准，并为年轻的研究人员提供了知识培养精力的年轻人的教育和职业，从而吸引了机器的知识性化学知识。
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.
