论文标题
在2020年代成为贝叶斯人：现代应用贝叶斯统计的实践中的机会和挑战
Being Bayesian in the 2020s: opportunities and challenges in the practice of modern applied Bayesian statistics
论文作者
论文摘要
在过去三十年中，基于哲学，理论，方法和计算的强大基础，贝叶斯的方法现在是大多数统计学家和数据科学家的工具包的组成部分。无论他们是专门的贝叶斯人还是机会主义者，应用专业人员现在都可以从贝叶斯范式带来的许多好处。在本文中，我们谈到了应用贝叶斯统计数据中的六个现代机遇和挑战：智能数据收集，新数据源，联合分析，隐式模型的推断，模型传输和有目的的软件产品。
Building on a strong foundation of philosophy, theory, methods and computation over the past three decades, Bayesian approaches are now an integral part of the toolkit for most statisticians and data scientists. Whether they are dedicated Bayesians or opportunistic users, applied professionals can now reap many of the benefits afforded by the Bayesian paradigm. In this paper, we touch on six modern opportunities and challenges in applied Bayesian statistics: intelligent data collection, new data sources, federated analysis, inference for implicit models, model transfer and purposeful software products.
