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Alpha Beta Crown ⭐ 205

alpha-beta-CROWN: An Efficient, Scalable and GPU Accelerated Neural Network Verifier (winner of VNN-COMP 2021, 2022, and 2023)

Detecting Adversarial Samples ⭐ 70

Code for "Detecting Adversarial Samples from Artifacts" (Feinman et al., 2017)

Denoised Smoothing ⭐ 69

Provably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs

Wasserstein Introspective Neural Networks (CVPR 2018 Oral)

Project page for our paper: Interpreting Adversarially Trained Convolutional Neural Networks

Adversarial Vision Challenge ⭐ 36

NIPS Adversarial Vision Challenge

Ijcnn19attacks ⭐ 29

Adversarial Attacks on Deep Neural Networks for Time Series Classification

Tf Squeezenet ⭐ 27

TensorFlow version of SqueezeNet with converted pretrained weights

Robust Nets ⭐ 14

Official implementation of the paper "Solving Inverse Problems With Deep Neural Networks - Robustness Included?" by M. Genzel, J. Macdonald, and M. März (2020).

Lgv Geometric Transferability ⭐ 9

Source of the ECCV22 paper "LGV: Boosting Adversarial Example Transferability from Large Geometric Vicinity"

Linear Region Attack ⭐ 8

A powerful white-box adversarial attack that exploits knowledge about the geometry of neural networks to find minimal adversarial perturbations without doing gradient descent

Adversarial Frontier Stitching ⭐ 7

Implementation of "Adversarial Frontier Stitching for Remote Neural Network Watermarking" in TensorFlow.

Ensemble_detect_adv ⭐ 6

Training Ensembles to Detect Adversarial Examples

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