Alternatives and similar repositories for minmax-adv

Users that are interested in minmax-adv are comparing it to the libraries listed below

• kenny-co / sgd-uap-torch
  Universal Adversarial Perturbations (UAPs) for PyTorch
  ☆49Updated 4 years ago
• bymavis / CAS_ICLR2021
  ☆58Updated 3 years ago
• jiaxiaojunQAQ / FGSM-SDI
  Code for Boosting fast adversarial training with learnable adversarial initialization (TIP2022)
  ☆29Updated 2 years ago
• qizhangli / linbp-attack
  Code for our NeurIPS 2020 paper Backpropagating Linearly Improves Transferability of Adversarial Examples.
  ☆42Updated 2 years ago
• ermongroup / ODS
  Code for "Diversity can be Transferred: Output Diversification for White- and Black-box Attacks"
  ☆53Updated 4 years ago
• dongyp13 / Adversarial-Distributional-Training
  Adversarial Distributional Training (NeurIPS 2020)
  ☆63Updated 4 years ago
• goldblum / AdversariallyRobustDistillation
  Pytorch implementation of Adversarially Robust Distillation (ARD)
  ☆59Updated 6 years ago
• dongyp13 / memorization-AT
  ☆21Updated 3 years ago
• csdongxian / skip-connections-matter
  Codes for ICLR 2020 paper "Skip Connections Matter: On the Transferability of Adversarial Examples Generated with ResNets"
  ☆70Updated 4 years ago
• val-iisc / Hard-Label-Model-Stealing
  ☆31Updated 3 years ago
• cassidylaidlaw / ReColorAdv
  ReColorAdv and other attacks from the NeurIPS 2019 paper "Functional Adversarial Attacks"
  ☆38Updated 3 years ago
• TransEmbedBA / TREMBA
  Code for Black-Box Adversarial Attack with Transferable Model-based Embedding
  ☆58Updated 5 years ago
• Muzammal-Naseer / NRP
  Official repository for "A Self-supervised Approach for Adversarial Robustness" (CVPR 2020--Oral)
  ☆100Updated 4 years ago
• krishnakanthnakka / Transferable_Perturbations
  [NeurIPS2021] Code Release of Learning Transferable Perturbations
  ☆28Updated 9 months ago
• Alan-Qin / Transfer_attack_RAP
  Boosting the Transferability of Adversarial Attacks with Reverse Adversarial Perturbation (NeurIPS 2022)
  ☆33Updated 2 years ago
• hsouri / Sleeper-Agent
  ☆66Updated last year
• val-iisc / GAMA-GAT
  Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses, NeurIPS Spotlight 2020
  ☆27Updated 4 years ago
• zjysteven / DVERGE
  [NeurIPS'20 Oral] DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of Ensembles
  ☆56Updated 3 years ago
• xherdan76 / A-Unified-Approach-to-Interpreting-and-Boosting-Adversarial-Transferability
  A Unified Approach to Interpreting and Boosting Adversarial Transferability (ICLR2021)
  ☆31Updated 3 years ago
• AI-secure / Robustness-Against-Backdoor-Attacks
  RAB: Provable Robustness Against Backdoor Attacks
  ☆39Updated last year
• whj363636 / Self-Ensemble-Adversarial-Training
  SEAT
  ☆21Updated last year
• zjfheart / Geometry-aware-Instance-reweighted-Adversarial-Training
  the paper "Geometry-aware Instance-reweighted Adversarial Training" ICLR 2021 oral
  ☆59Updated 4 years ago
• zibojia / RSLAD
  This is the official code for "Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better"
  ☆42Updated 4 years ago
• machanic / SimulatorAttack
  The official implementation of CVPR 2021 paper "Simulating Unknown Target Models for Query-Efficient Black-box Attacks"
  ☆59Updated 4 years ago
• liuye6666 / adaptive_auto_attack
  Adversarial Robustness, White-box, Adversarial Attack
  ☆51Updated 3 years ago
• HanxunH / RobustWRN
  [NeurIPS2021] Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks
  ☆34Updated last year
• rkteddy / channel-Lipschitzness-based-pruning
  Source code for ECCV 2022 Poster: Data-free Backdoor Removal based on Channel Lipschitzness
  ☆34Updated 2 years ago
• point0bar1 / ebm-defense
  PyTorch implementation of BPDA+EOT attack to evaluate adversarial defense with an EBM
  ☆25Updated 5 years ago
• ash-aldujaili / blackbox-adv-examples-signhunter
  A repository for the query-efficient black-box attack, SignHunter
  ☆23Updated 5 years ago
• superrrpotato / Defending-Neural-Backdoors-via-Generative-Distribution-Modeling
  The code is for our NeurIPS 2019 paper: https://arxiv.org/abs/1910.04749
  ☆34Updated 5 years ago