论文标题
热物理学和太空天气预报中的机器学习：发现和建议的白皮书
Machine Learning in Heliophysics and Space Weather Forecasting: A White Paper of Findings and Recommendations
论文作者
论文摘要
这份白皮书的作者于2020年1月16日至17日在新泽西州新泽西州纽瓦克市的新泽西州纽瓦克开会，举办了为期两天的研讨会，将一组热电学家，数据提供者，专家建模者和计算机/数据科学家汇集在一起。他们的目标是讨论用于在热物理学中应用机器和/或深度学习技术应用于数据分析，建模和预测的关键发展和前景，并制定了该领域进一步发展的策略。研讨会结合了一组全体会议，其中包括受邀的介绍性演讲，并与一系列公开的讨论会议交织在一起。讨论的结果封装在这份白皮书中，还列出了参与者商定的顶级建议列表。
The authors of this white paper met on 16-17 January 2020 at the New Jersey Institute of Technology, Newark, NJ, for a 2-day workshop that brought together a group of heliophysicists, data providers, expert modelers, and computer/data scientists. Their objective was to discuss critical developments and prospects of the application of machine and/or deep learning techniques for data analysis, modeling and forecasting in Heliophysics, and to shape a strategy for further developments in the field. The workshop combined a set of plenary sessions featuring invited introductory talks interleaved with a set of open discussion sessions. The outcome of the discussion is encapsulated in this white paper that also features a top-level list of recommendations agreed by participants.
