library PIL: rotating, color inverting, posterizing (reducing pixel bits), solarizing (inverting colors above a threshold), etc. - Plus Cutout and SamplePairing - 10 magnitudes, 11 probabilities - Trained using Recurrent Neural Network trained with Proximal Policy Optimization Ekin DC, Barret Z, Dandelion M, Vijay V, Quoc VL. AutoAugment: learning augmentation policies from data. ArXiv preprint. 2018.