Alternatives and similar repositories for pytorch-classification-advprop:

Users that are interested in pytorch-classification-advprop are comparing it to the libraries listed below

• VITA-Group / Adv-SS-Pretraining
  [CVPR 2020] Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning
  ☆85Updated 3 years ago
• VITA-Group / Adversarial-Contrastive-Learning
  [NeurIPS 2020] “ Robust Pre-Training by Adversarial Contrastive Learning”, Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang
  ☆115Updated 3 years ago
• cihangxie / SmoothAdversarialTraining
  Smooth Adversarial Training
  ☆67Updated 4 years ago
• meijieru / fast_advprop
  [ICLR 2022]: Fast AdvProp
  ☆34Updated 3 years ago
• garyzhao / ME-ADA
  "Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness" (NeurIPS 2020).
  ☆50Updated 4 years ago
• imrahulr / adversarial_robustness_pytorch
  Unofficial implementation of the DeepMind papers "Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples…
  ☆95Updated 3 years ago
• snu-mllab / Co-Mixup
  Official PyTorch implementation of "Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity" (ICLR'21 Oral)
  ☆103Updated 3 years ago
• LiYingwei / ShapeTextureDebiasedTraining
  Code and models for the paper Shape-Texture Debiased Neural Network Training (ICLR 2021)
  ☆108Updated last year
• hankook / SLA
  Self-supervised Label Augmentation via Input Transformations (ICML 2020)
  ☆104Updated 4 years ago
• RulinShao / on-the-adversarial-robustness-of-visual-transformer
  Code for the paper "On the Adversarial Robustness of Visual Transformers"
  ☆56Updated 3 years ago
• LijieFan / AdvCL
  [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”
  ☆48Updated 3 years ago
• tml-epfl / understanding-fast-adv-training
  Understanding and Improving Fast Adversarial Training [NeurIPS 2020]
  ☆95Updated 3 years ago
• P2333 / Mixup-Inference
  Further improve robustness of mixup-trained models in inference (ICLR 2020)
  ☆60Updated 4 years ago
• PKUAI26 / AT-CNN
  Project page for our paper: Interpreting Adversarially Trained Convolutional Neural Networks
  ☆66Updated 5 years ago
• YU1ut / JointOptimization
  Code for 'Joint Optimization Framework for Learning with Noisy Labels'
  ☆38Updated 6 years ago
• bfshi / InfoDrop
  Code for our paper "Informative Dropout for Robust Representation Learning: A Shape-bias Perspective" (ICML 2020)
  ☆125Updated 2 years ago
• VainF / Data-Free-Adversarial-Distillation
  Code and pretrained models for paper: Data-Free Adversarial Distillation
  ☆95Updated 2 years ago
• prithv1 / DMG
  Code for our ECCV paper -- "Learning to Balance Specificity and Invariance for In and Out of Domain Generalization"
  ☆55Updated 4 years ago
• Muzammal-Naseer / TTP
  Official repository for "On Generating Transferable Targeted Perturbations" (ICCV 2021)
  ☆60Updated 2 years ago
• dvlab-research / LBGAT
  Learnable Boundary Guided Adversarial Training (ICCV2021)
  ☆36Updated 3 months ago
• kai-wen-yang / CD-VAE
  [NeurIPS 2021] "Class-Disentanglement and Applications in Adversarial Detection and Defense"
  ☆44Updated 3 years ago
• deeplearning-wisc / react
  Code for NeurIPS 2021 paper "ReAct: Out-of-distribution Detection With Rectified Activations"
  ☆52Updated 3 years ago
• aamir-mustafa / pcl-adversarial-defense
  Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks, in ICCV 2019
  ☆59Updated 5 years ago
• youjiangxu / FaMUS
  ☆28Updated 3 years ago
• LayneH / self-adaptive-training
  [TPAMI2022 & NeurIPS2020] Official implementation of Self-Adaptive Training
  ☆129Updated 3 years ago
• wutong16 / Adversarial_Long-Tail
  [ CVPR 2021 Oral ] Pytorch implementation for "Adversarial Robustness under Long-Tailed Distribution"
  ☆101Updated 3 years ago
• dvlab-research / MiSLAS
  Improving Calibration for Long-Tailed Recognition (CVPR2021)
  ☆147Updated 3 years ago
• VITA-Group / Nasty-Teacher
  [ICLR 2021 Spotlight Oral] "Undistillable: Making A Nasty Teacher That CANNOT teach students", Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Che…
  ☆81Updated 3 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
• lvyilin / pytorch-fgvc-dataset
  PyTorch custom dataset APIs -- CUB-200-2011, Stanford Dogs, Stanford Cars, FGVC Aircraft, NABirds, Tiny ImageNet, iNaturalist2017
  ☆155Updated 2 years ago