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A PyTorch implementation of the method found in "Adversarially Robust Few-Shot Learning: A Meta-Learning Approach"

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Adversarially Robust Few-Shot Learning: A Meta-Learning Approach

Micah Goldblum, Liam Fowl, Tom Goldstein

This repository contains PyTorch code for adversarial querying with ProtoNet, R2-D2, and MetaOptNet. Adversarial querying is an algorithm for producing robust meta-learners. More can be found in our paper. We adapt models and data loading from here.

Prerequisites:

  • Python2
  • PyTorch
  • CUDA

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A PyTorch implementation of the method found in "Adversarially Robust Few-Shot Learning: A Meta-Learning Approach"

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