DSE-MSU/DeepRobust
A PyTorch library for adversarial attacks and defenses on image and graph models.
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DeepRobust is a PyTorch adversarial library that implements attack and defense methods targeting deep learning models. It covers both image-based and graph-based domains, including graph neural networks and graph convolutional networks. The library enables researchers to evaluate model robustness by generating adversarial examples and testing defense strategies.
Frequently asked
- What is DSE-MSU/DeepRobust?
- A PyTorch library for adversarial attacks and defenses on image and graph models.
- Is DeepRobust open source?
- Yes — DSE-MSU/DeepRobust is open source, released under the MIT license.
- What language is DeepRobust written in?
- DSE-MSU/DeepRobust is primarily written in Python.
- How popular is DeepRobust?
- DSE-MSU/DeepRobust has 1.1k stars on GitHub.
- Where can I find DeepRobust?
- DSE-MSU/DeepRobust is on GitHub at https://github.com/DSE-MSU/DeepRobust.