How to Make Machine Learning Work in A Data-Limited System (8 of 8) (VIDEO)

American Association for the Advancement of Science (AAAS)

Caption

Animation that outlines the steps in the project for a general audience. This material relates to a paper that appeared in the April 26th, 2019, issue of Science Advances, published by AAAS. The paper, by J. Hoffmann at Harvard University in Cambridge, MA, and colleagues was titled, "Machine learning in a data-limited regime: Augmenting experiments with synthetic data uncovers order in crumpled sheets."

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Jordan Hoffmann, Yohai Bar-Sinai, Shruti Mishra, and Lisa Lee

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