Alternatives and similar repositories for MAIL:

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

• kai-wen-yang / CD-VAE
  [NeurIPS 2021] "Class-Disentanglement and Applications in Adversarial Detection and Defense"
  ☆44Updated 3 years ago
• zjfheart / Geometry-aware-Instance-reweighted-Adversarial-Training
  the paper "Geometry-aware Instance-reweighted Adversarial Training" ICLR 2021 oral
  ☆59Updated 3 years ago
• ZFancy / IAD
  [ICLR 2022] Reliable Adversarial Distillation with Unreliable Teachers
  ☆21Updated 3 years ago
• LijieFan / AdvCL
  [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”
  ☆48Updated 3 years ago
• Saehyung-Lee / cifar10_challenge
  Code for the CVPR 2020 article "Adversarial Vertex mixup: Toward Better Adversarially Robust Generalization"
  ☆13Updated 4 years ago
• ChaojianYu / Robust-Weight-Perturbation
  Implementation for <Robust Weight Perturbation for Adversarial Training> in IJCAI'22.
  ☆14Updated 2 years ago
• HanshuYAN / CIFS
  CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection
  ☆20Updated 3 years ago
• PKU-ML / CFA
  ☆20Updated last year
• kaiwenzha / contrastive-poisoning
  [ICLR 2023, Spotlight] Indiscriminate Poisoning Attacks on Unsupervised Contrastive Learning
  ☆30Updated last year
• ChaojianYu / Understanding-Robust-Overfitting
  Implementation for <Understanding Robust Overftting of Adversarial Training and Beyond> in ICML'22.
  ☆12Updated 2 years ago
• QizhouWang / DOE
  ☆25Updated last year
• xherdan76 / A-Unified-Approach-to-Interpreting-and-Boosting-Adversarial-Transferability
  A Unified Approach to Interpreting and Boosting Adversarial Transferability (ICLR2021)
  ☆29Updated 2 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…
  ☆46Updated 3 years ago
• dwDavidxd / ARN
  Towards Defending against Adversarial Examples via Attack-Invariant Features
  ☆10Updated last year
• zibojia / RSLAD
  This is the official code for "Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better"
  ☆39Updated 3 years ago
• val-iisc / NuAT
  Towards Efficient and Effective Adversarial Training, NeurIPS 2021
  ☆17Updated 3 years ago
• inspire-group / tta_risk
  ☆11Updated last year
• val-iisc / DAJAT
  Official Code for Efficient and Effective Augmentation Strategy for Adversarial Training (NeurIPS-2022)
  ☆16Updated last year
• jkatzsam / woods_ood
  ☆16Updated 2 years ago
• PKU-ML / DYNACL
  [ICLR 2023] Official repository of the paper "Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning"
  ☆18Updated 2 years ago
• cychomatica / One-Pixel-Shotcut
  One-Pixel Shortcut: on the Learning Preference of Deep Neural Networks (ICLR 2023 Spotlight)
  ☆13Updated 2 years ago
• jiamingzhang94 / Unlearnable-Clusters
  CVPR2023: Unlearnable Clusters: Towards Label-agnostic Unlearnable Examples
  ☆21Updated last year
• TLMichael / Delusive-Adversary
  [NeurIPS 2021] Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training
  ☆31Updated 3 years ago
• nblt / Sub-AT
  [CVPR 2022 oral] Subspace Adversarial Training
  ☆26Updated last year
• Haoang97 / TOHAN
  Source code for NeurIPS 2021 paper "TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation".
  ☆9Updated 2 years ago
• dvlab-research / LBGAT
  Learnable Boundary Guided Adversarial Training (ICCV2021)
  ☆36Updated 3 months ago
• whj363636 / Self-Ensemble-Adversarial-Training
  SEAT
  ☆20Updated last year
• bymavis / CAS_ICLR2021
  ☆57Updated 2 years ago
• point0bar1 / ebm-defense
  PyTorch implementation of BPDA+EOT attack to evaluate adversarial defense with an EBM
  ☆24Updated 4 years ago
• jiaxiaojunQAQ / FGSM-PGI
  Code for Prior-Guided Adversarial Initialization for Fast Adversarial Training (ECCV2022)
  ☆26Updated 2 years ago