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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 sequentially fill the space of the outputs (responses or features). Several examples are given to show the advantages of the proposed method over the traditional input space-filling designs.