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[P] Robustness: a library for training and experimenting with standard and robust training

Hi all,

Robustness is a library we made for use in our research that has evolved over several projects we have used it in. The result is a library for standard and robust (adversarial) training that is designed to be super extendible/customizable with very minimal effort. For example, the library allows us to train networks with custom loss functions, adversaries, logging, data loaders, etc, and also to perform a variety of input manipulation tasks using pretrained networks. Finally we provide a CLI interface for training standard and robust models.

Code is here: https://github.com/MadryLab/robustness

Full documentation, walkthroughs, and examples are here: https://robustness.readthedocs.io/

submitted by /u/andrew_ilyas
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.