综述人工智能在化学领域的进展，涵盖方法、应用与未来方向。
Survey on Recent Progress of AI for Chemistry: Methods, Applications, and Opportunities
- 从数据特征到表示方法，系统梳理化学AI的算法设计
- 覆盖多种任务模型，总结当前研究热点与技术路径
- 适合关注化学智能化的科研人员和交叉领域学者
人工智能技术的发展在多个领域带来革命性变化。特别是在利用AI辅助加速化学研究方面，已成为热门且快速发展的趋势，催生了众多突破性成果。本文从计算角度全面回顾化学领域当前的人工智能技术，涵盖方法设计的多个方面。首先讨论来自不同来源的数据特征，随后概述各类分子表示方法。接着，对领域内若干关键任务的现有模型进行综述，并最后指出若干亟需进一步关注的关键挑战。
原文摘要 · Abstract (English)
The development of artificial intelligence (AI) techniques has brought revolutionary changes across various realms. In particular, the use of AI-assisted methods to accelerate chemical research has become a popular and rapidly growing trend, leading to numerous groundbreaking works. In this paper, we provide a comprehensive review of current AI techniques in chemistry from a computational perspective, considering various aspects in the design of methods. We begin by discussing the characteristics of data from diverse sources, followed by an overview of various representation methods. Next, we review existing models for several topical tasks in the field, and conclude by highlighting some key challenges that warrant further attention.
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