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Search results for robustness adversarial examples

adversarial-examples x

17 search results found

Advertorch ⭐ 1,271

A Toolbox for Adversarial Robustness Research

Natural Adv Examples ⭐ 559

A Harder ImageNet Test Set (CVPR 2021)

Photoguard ⭐ 431

Raising the Cost of Malicious AI-Powered Image Editing

Awesome Graph Attack Papers ⭐ 315

Adversarial attacks and defenses on Graph Neural Networks.

Auto_lirpa ⭐ 265

auto_LiRPA: An Automatic Linear Relaxation based Perturbation Analysis Library for Neural Networks and General Computational Graphs

Adversarial Explainable Ai ⭐ 235

💡 Adversarial attacks on explanations and how to defend them

Alpha Beta Crown ⭐ 205

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

Free_adv_train ⭐ 95

Official TensorFlow Implementation of Adversarial Training for Free! which trains robust models at no extra cost compared to natural training.

Pre Training ⭐ 79

Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)

[CVPR 2020] When NAS Meets Robustness: In Search of Robust Architectures against Adversarial Attacks

Understanding Fast Adv Training ⭐ 67

Understanding and Improving Fast Adversarial Training [NeurIPS 2020]

Crown Ibp ⭐ 64

Certified defense to adversarial examples using CROWN and IBP. Also includes GPU implementation of CROWN verification algorithm (in PyTorch).

Robust Local Lipschitz ⭐ 50

A Closer Look at Accuracy vs. Robustness

Adversarial Vision Challenge ⭐ 36

NIPS Adversarial Vision Challenge

[ICML 2019] ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation

Bert Probe ⭐ 16

BERT Probe: A python package for probing attention based robustness to character and word based adversarial evaluation. Also, with recipes of implicit and explicit defenses against character-level attacks.

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).

Whoneedsadversaries ⭐ 8

Code implementing the experiments described in the NeurIPS 2018 paper "With Friends Like These, Who Needs Adversaries?".

Lipschitz-Certifiable Training with a Tight Outer Bound [NeurIPS 2020] | BCP (Box Constraint Propagation) | ⚡💪🛡️

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