论文标题
集成行星科学的机器学习：未来十年的观点
Integrating Machine Learning for Planetary Science: Perspectives for the Next Decade
论文作者
论文摘要
机器学习（ML）方法可以扩展我们的构造能力，并从大型数据集中获取见解。尽管行星观测的数量增加了，但与其他科学相比，我们的领域很少有ML的应用。为了支持这些方法，我们提出了十个建议，以加强行星科学中数据丰富的未来。
Machine learning (ML) methods can expand our ability to construct, and draw insight from large datasets. Despite the increasing volume of planetary observations, our field has seen few applications of ML in comparison to other sciences. To support these methods, we propose ten recommendations for bolstering a data-rich future in planetary science.
