The application of machine learning to materials research has seen remarkable transformations in a relatively short amount of time. Not too long ago, machine learning in materials was considered a niche field with relatively few publications. Today, with many thousands of articles being published yearly, keeping track of the various developments has become a major challenge. The citation analysis presented in this article provides clues as to the fuel behind the rapid advancements. New publications are built upon algorithms and tools not only from within the materials science community but also from the computer science community. This has led to rapid advancements in performance on benchmark tasks such as those in the matbench protocol.