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Search results for adversarial robustness
adversarial-robustness
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33 search results found
Auto Attack
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587
Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"
Robustbench
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566
RobustBench: a standardized adversarial robustness benchmark [NeurIPS'21 Benchmarks and Datasets Track]
Ares
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413
A Python library for adversarial machine learning focusing on benchmarking adversarial robustness.
Easyrobust
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293
EasyRobust: an Easy-to-use library for state-of-the-art Robust Computer Vision Research with PyTorch.
Alpha Beta Crown
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205
alpha-beta-CROWN: An Efficient, Scalable and GPU Accelerated Neural Network Verifier (winner of VNN-COMP 2021, 2022, and 2023)
Self Adaptive Training
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104
Official implementation of the NeurIPS'2020 paper 'Self-Adaptive Training: beyond Empirical Risk Minimization'
Infobert
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81
[ICLR 2021] "InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective" by Boxin Wang, Shuohang Wang, Yu Cheng, Zhe Gan, Ruoxi Jia, Bo Li, Jingjing Liu
Denoised Smoothing
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69
Provably defending pretrained classifiers including the Azure, Google, AWS, and Clarifai APIs
Adv Ss Pretraining
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65
[CVPR 2020] Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning
Aug Nerf
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65
[CVPR 2022] "Aug-NeRF: Training Stronger Neural Radiance Fields with Triple-Level Physically-Grounded Augmentations" by Tianlong Chen*, Peihao Wang*, Zhiwen Fan, Zhangyang Wang
Dverge
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43
Pytorch implementation of our NeurIPS'20 *Oral* paper "DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of Ensembles" https://papers.nips.cc/paper/2020/hash/3ad7c2ebb96
Featurescatter
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39
Feature Scattering Adversarial Training
Adversarial_robustness_pytorch
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37
Unofficial implementation of the DeepMind papers "Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples" & "Fixing Data Augmentation to Improve Adversarial Robustness" in PyTorch
Square Attack
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27
Square Attack: a query-efficient black-box adversarial attack via random search [ECCV 2020]
L_inf Dist Net
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24
This is the official github repo for training L_inf dist nets with high certified accuracy.
Lnets
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24
Lipschitz Neural Networks described in "Sorting Out Lipschitz Function Approximation" (ICML 2019).
Patch Fool
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22
[ICLR 2022] "Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?" by Yonggan Fu, Shunyao Zhang, Shang Wu, Cheng Wan, Yingyan Lin
Triple Wins
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22
[ICLR 2020] ”Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference“
Robrank
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18
Adversarial Attack and Defense in Deep Ranking, arXiv:2106.03614
Fab Attack
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18
Code for FAB-attack
Robust Residual Network
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15
Revisiting Residual Networks for Adversarial Robustness: An Architectural Perspective
Dkl
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15
Decoupled Kullback-Leibler Divergence Loss (DKL)
Hat
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14
Helper-based Adversarial Training: Reducing Excessive Margin to Achieve a Better Accuracy vs. Robustness Trade-off
Robust Finetuning
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13
Code relative to "Adversarial robustness against multiple and single $l_p$-threat models via quick fine-tuning of robust classifiers"
Md_attacks
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9
Imbalanced Gradients: A New Cause of Overestimated Adversarial Robustness. (MD attacks)
Targeted Adversarial Perturbations Monocular Depth
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9
PyTorch implementation of Targeted Adversarial Perturbations for Monocular Depth Predictions (in NeurIPS 2020)
Mair
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8
PyTorch implementation of adversarial defenses [Fantastic Robustness Measures: The Secrets of Robust Generalization, NeurIPS 2023].
Privacyattack_at_fl
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7
A privacy attack that exploits Adversarial Training models to compromise the privacy of Federated Learning systems.
Reliable_gnn_via_robust_aggregation
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7
This repository contains the official implementation of the paper "Reliable Graph Neural Networks via Robust Aggregation" (NeurIPS, 2020).
L_inf Dist Net V2
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6
Training L_inf-dist-net with faster acceleration and better training strategies
Adversarial_robustness_zsl
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5
[ECCV 2020 AROW Workshop] A Deep Dive into Adversarial Robustness in Zero-Shot Learning
Sparseadversarialtraining
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5
Code for "Training Adversarially Robust Sparse Networks via Bayesian Connectivity Sampling" [ICML 2021]
Double Win Lth
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5
[ICML 2022] "Data-Efficient Double-Win Lottery Tickets from Robust Pre-training" by Tianlong Chen, Zhenyu Zhang, Sijia Liu, Yang Zhang, Shiyu Chang, Zhangyang Wang
Related Searches
Python Adversarial Robustness (25)
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Deep Learning Adversarial Robustness (4)
Neural Network Adversarial Robustness (4)
Pytorch Adversarial Robustness (4)
Paper Adversarial Robustness (3)
Image Classification Adversarial Robustness (3)
Jupyter Notebook Adversarial Robustness (3)
Generalization Adversarial Robustness (3)
1-33 of 33 search results
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