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Hard to keep up with @tanmingxing @quocleix and team! I just finished making it through EfficientDet and Noisy Student and now have AdvProp, w/ a quietly released update of all EfficientNet weights, incl a new B8 model spec.https://github.com/tensorflow/tpu/tree/master/models/official/efficientnet …
The TLDR of the paper; use adversarial examples as training data augmentation, maintain separate BatchNorm for normal vs adversarial examples. Neat. As usual I've ported & tested #PyTorch weightshttps://github.com/rwightman/gen-efficientnet-pytorch …
Could you please point to the paper on adverserial auto augment?
Ah it was in the repo https://arxiv.org/abs/1911.09665 , in case anyone else was looking.
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