Space-filling designs are commonly used in computer experiments to fill the space of inputs so that the input-output relationship can be accurately estimated. However, in certain applications such as inverse design or feature-based modeling, the aim is to fill the response or feature space. In this article, we propose a new experimental design framework that aims to fill the space of the outputs (responses or features). The design is adaptive and model-free, and therefore is expected to be robust to different kinds of modeling choices and input-output relationships. Several examples are given to show the advantages of the proposed method over the traditional input space-filling designs.

翻译：空间填充设计在计算机实验中常用于填充输入空间，以便精确估计输入-输出关系。然而，在逆设计或基于特征的建模等特定应用中，目标在于填充响应或特征空间。本文提出了一种新的实验设计框架，旨在填充输出（响应或特征）空间。该设计是自适应且无模型的，因此预期对不同类型的建模选择和输入-输出关系具有鲁棒性。通过若干实例展示了所提方法相较于传统输入空间填充设计的优势。