-By Jerry O. Talton Intel Corporation, Lingfeng, Yang Stanford University, Ranjitha Kumar Stanford University, Maxine Lim Stanford University, Noah D. Goodman Stanford University, Radom´ır Mech ˇ Adobe Corporation This blog is extension to the earlier blog . Paper Link ABSTRACT Design patterns have proven useful in many creative fields, providing content creators with archetypal, reusable guidelines to leverage in projects. Creating such patterns, however, is a time-consuming, manual process, typically relegated to a few experts in any given domain. In this paper, we describe an algorithmic method for learning design patterns directly from data using techniques from natural language processing and structured concept learning. Given a set of labeled, hierarchical designs as input, we induce a probabilistic formal grammar over these exemplars. Once learned, this grammar encodes a set of generative rules for the class of designs, which can be sampled to synthesize ...