论文标题
多阶段管道的不确定性下的决策：基于基准筛选策略的模拟研究
Decision-Making Under Uncertainty for Multi-stage Pipelines: Simulation Studies to Benchmark Screening Strategies
论文作者
论文摘要
Multi-stage screening pipelines are ubiquitous throughout experimental and computational science.开发筛选管道的大部分精力都集中在改善生成方法或替代模型上，以试图使每个筛选步骤对特定应用有效。 Little focus has been placed on characterizing generic screening pipeline performance with respect to the problem or problem parameters. Here, we develop models and algorithms to codify and simulate features and properties of the screening procedure in general.我们概述并建模常见问题设置以及在不确定性下执行决策的潜在机会，以优化筛选管道的执行。 We then illustrate the models and algorithms through several simulation studies.我们最终展示了这些研究如何在问题参数方面量化筛选管道性能，特别是确定了阶段协方差结构的重要性。我们展示了这种结构如何导致质量不同的筛选行为，以及在某些情况下，筛选甚至比随机的效果更糟。
Multi-stage screening pipelines are ubiquitous throughout experimental and computational science. Much of the effort in developing screening pipelines focuses on improving generative methods or surrogate models in an attempt to make each screening step effective for a specific application. Little focus has been placed on characterizing generic screening pipeline performance with respect to the problem or problem parameters. Here, we develop models and algorithms to codify and simulate features and properties of the screening procedure in general. We outline and model common problem settings and potential opportunities to perform decision-making under uncertainty to optimize the execution of screening pipelines. We then illustrate the models and algorithms through several simulation studies. We finally show how such studies can provide a quantification of the screening pipeline performance with respect to problem parameters, specifically identifying the significance of stage-wise covariance structure. We show how such structure can lead to qualitatively different screening behaviors, and how screening can even perform worse than random in some cases.
