论文标题
计算因果推断
Computational Causal Inference
论文作者
论文摘要
我们将计算因果推断作为因果推理，算法设计和数值计算的跨学科领域。该领域旨在开发专门从事因果推理的软件，该软件可以以表现，一般和健壮的方式分析具有多种因果效应的大规模数据集。对软件的重点改善了研究敏捷性，并使因果推断可以轻松地集成到大型工程系统中。特别是，我们使用计算因果推论来加深因果推理，在线实验和算法决策之间的关系。 本文描述了新领域，需求，可伸缩性的机会，开放挑战，并开始讨论社区如何团结起来解决因果关系推理和决策的挑战。
We introduce computational causal inference as an interdisciplinary field across causal inference, algorithms design and numerical computing. The field aims to develop software specializing in causal inference that can analyze massive datasets with a variety of causal effects, in a performant, general, and robust way. The focus on software improves research agility, and enables causal inference to be easily integrated into large engineering systems. In particular, we use computational causal inference to deepen the relationship between causal inference, online experimentation, and algorithmic decision making. This paper describes the new field, the demand, opportunities for scalability, open challenges, and begins the discussion for how the community can unite to solve challenges for scaling causal inference and decision making.
