TECHNIQUES FOR GENERATING DESIGNS THAT REFLECT STYLISTIC PREFERENCES

In various embodiments, a stylization application generates designs that reflect stylistic preferences. In operation, the stylization application computes characterization information based on a first design and a trained machine-learning model that maps one or more designs to characterization information associated with one or more styles. The stylization application then computes a style score based on the characterization information and a target style that is included in the one or more styles. Subsequently, the stylization application generates a second design based on the style score, where the second design is more representative of the target style than the first design. Advantageously, because the stylization application can substantially increase the number of designs that can be generated based on the target style in a given amount of time, relative to more manual prior art techniques, the overall quality of the design ultimately selected for production can be improved.