Alternatives and similar repositories for adp

Users that are interested in adp are comparing it to the libraries listed below

• point0bar1 / ebm-defense
  PyTorch implementation of BPDA+EOT attack to evaluate adversarial defense with an EBM
  ☆25Updated 5 years ago
• ethz-spylab / diffusion_denoised_smoothing
  Certified robustness "for free" using off-the-shelf diffusion models and classifiers
  ☆42Updated 2 years ago
• wzekai99 / DM-Improves-AT
  Code for the paper "Better Diffusion Models Further Improve Adversarial Training" (ICML 2023)
  ☆141Updated last year
• nmndeep / revisiting-at
  [NeurIPS 2023] Code for the paper "Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threa…
  ☆38Updated 7 months ago
• imrahulr / adversarial_robustness_pytorch
  Unofficial implementation of the DeepMind papers "Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples…
  ☆97Updated 3 years ago
• YisenWang / MART
  Code for ICLR2020 "Improving Adversarial Robustness Requires Revisiting Misclassified Examples"
  ☆150Updated 4 years ago
• zjfheart / Geometry-aware-Instance-reweighted-Adversarial-Training
  the paper "Geometry-aware Instance-reweighted Adversarial Training" ICLR 2021 oral
  ☆59Updated 4 years ago
• JinyiW / GuidedDiffusionPur
  ☆60Updated last year
• inspire-group / proxy-distributions
  [ICLR 2022 official code] Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?
  ☆29Updated 3 years ago
• cassidylaidlaw / perceptual-advex
  Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".
  ☆55Updated 3 years ago
• locuslab / robust_overfitting
  ☆158Updated 4 years ago
• VITA-Group / Alleviate-Robust-Overfitting
  [ICLR 2021] "Robust Overfitting may be mitigated by properly learned smoothening" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, Shiyu Chan…
  ☆47Updated 3 years ago
• xherdan76 / A-Unified-Approach-to-Interpreting-and-Boosting-Adversarial-Transferability
  A Unified Approach to Interpreting and Boosting Adversarial Transferability (ICLR2021)
  ☆29Updated 3 years ago
• NYU-DICE-Lab / circumventing-concept-erasure
  ☆20Updated last year
• P2333 / SCORE
  A Self-Consistent Robust Error (ICML 2022)
  ☆68Updated 2 years ago
• lhfowl / adversarial_poisons
  ☆51Updated 3 years ago
• Haichao-Zhang / FeatureScatter
  Feature Scattering Adversarial Training (NeurIPS19)
  ☆73Updated last year
• alinlab / consistency-adversarial
  Consistency Regularization for Adversarial Robustness (AAAI 2022)
  ☆53Updated 3 years ago
• RulinShao / on-the-adversarial-robustness-of-visual-transformer
  Code for the paper "On the Adversarial Robustness of Visual Transformers"
  ☆58Updated 3 years ago
• cassidylaidlaw / ReColorAdv
  ReColorAdv and other attacks from the NeurIPS 2019 paper "Functional Adversarial Attacks"
  ☆37Updated 3 years ago
• watml / fast-wasserstein-adversarial
  Implementation of Wasserstein adversarial attacks.
  ☆23Updated 4 years ago
• chenweixin107 / TrojDiff
  ☆58Updated 2 years ago
• ml-postech / robust-evaluation-of-diffusion-based-purification
  [ICCV 2023 Oral] Official implementation of "Robust Evaluation of Diffusion-Based Adversarial Purification"
  ☆25Updated last year
• dedeswim / vits-robustness-torch
  Code for the paper "A Light Recipe to Train Robust Vision Transformers" [SaTML 2023]
  ☆52Updated 2 years ago
• kai-wen-yang / CD-VAE
  [NeurIPS 2021] "Class-Disentanglement and Applications in Adversarial Detection and Defense"
  ☆45Updated 3 years ago
• whj363636 / Self-Ensemble-Adversarial-Training
  SEAT
  ☆21Updated last year
• v-wangg / OrthogonalPGD
  ☆22Updated 3 years ago
• umd-huang-lab / Dynamics-Aware-Robust-Training
  ICLR 2023 paper "Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness" by Yuancheng Xu, Yanchao Sun, Micah Gold…
  ☆25Updated 2 years ago
• qizhangli / linbp-attack
  Code for our NeurIPS 2020 paper Backpropagating Linearly Improves Transferability of Adversarial Examples.
  ☆42Updated 2 years ago
• tml-epfl / understanding-fast-adv-training
  Understanding and Improving Fast Adversarial Training [NeurIPS 2020]
  ☆95Updated 3 years ago