A Toolbox for Adversarial Robustness Research
Implementation of Papers on Adversarial Examples
[CIKM 2022] Self-supervision Meets Adversarial Perturbation: A Novel Framework for Anomaly Detection (PyTorch)
Code of our recently published attack FDA: Feature Disruptive Attack. Colab Notebook: https://colab.research.google.com/drive/1WhkKCrzFq5b7SNrbLUfdLVo5-WK5mLJh
PyTorch implementation of Targeted Adversarial Perturbations for Monocular Depth Predictions (in NeurIPS 2020)
PyTorch implementation of Stereopagnosia: Fooling Stereo Networks with Adversarial Perturbations (in AAAI 2021)
CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing (ACL 2022)
Course Project for EE782. IIT Bombay, Autumn 2019
Adversarial Attacks and Defenses via Image perturbations
Pytorch implementation of https://github.com/val-iisc/nag
Repository for final project of Data Mining Course
School AI semester project
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