3.6k citations · 10.6k across the 54 of their papers we have counts for
4 papers · 1 filter
Accelerated search and design of stretchable graphene kirigami using machine learning
Paul Z. Hanakata, Ekin D. Cubuk, David K. Campbell +1
Making kirigami-inspired cuts into a sheet has been shown to be an effective way of designing stretchable materials with metamorphic properties where the 2D shape can transform int…
Machine learning-assisted discovery of many new solid Li-ion conducting materials
Austin D. Sendek, Ekin D. Cubuk, Evan R. Antoniuk +3
We discover many new crystalline solid materials with fast single crystal Li ion conductivity at room temperature, discovered through density functional theory simulations guided b…
AutoAugment: Learning Augmentation Policies from Data
Ekin D. Cubuk, Barret Zoph, Dandelion Mane +2
Data augmentation is an effective technique for improving the accuracy of modern image classifiers. However, current data augmentation implementations are manually designed. In thi…
Machine learning determination of atomic dynamics at grain boundaries
Tristan A. Sharp, Spencer L. Thomas, Ekin D. Cubuk +3
In polycrystalline materials, grain boundaries are sites of enhanced atomic motion, but the complexity of the atomic structures within a grain boundary network makes it difficult t…