Alternatives and similar repositories for ibinn_imagenet

Users that are interested in ibinn_imagenet 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
• garyzhao / ME-ADA
  "Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness" (NeurIPS 2020).
  ☆51Updated 4 years ago
• hendrycks / pre-training
  Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)
  ☆100Updated 3 years ago
• human-analysis / MaxEnt-ARL
  PyTorch Implementation of CVPR'19 (oral) - Mitigating Information Leakage in Image Representations: A Maximum Entropy Approach
  ☆28Updated 5 years ago
• chingyaoc / fair-mixup
  ICLR 2021, Fair Mixup: Fairness via Interpolation
  ☆56Updated 3 years ago
• HaohanWang / PAR_experiments
  Learning Robust Global Representations by Penalizing Local Predictive Power (NeurIPS 2019))
  ☆18Updated 2 years ago
• PKUAI26 / AT-CNN
  Project page for our paper: Interpreting Adversarially Trained Convolutional Neural Networks
  ☆66Updated 6 years ago
• hankook / AugSelf
  ☆46Updated 3 years ago
• meijieru / fast_advprop
  [ICLR 2022]: Fast AdvProp
  ☆35Updated 3 years ago
• jason718 / semi-sup
  Code for paper "Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning", Ren et al., NeurIPS'20
  ☆25Updated 4 years ago
• bethgelab / game-of-noise
  Trained model weights, training and evaluation code from the paper "A simple way to make neural networks robust against diverse image cor…
  ☆61Updated 2 years ago
• P2333 / Rectified-Rejection
  Coupling rejection strategy against adversarial attacks (CVPR 2022)
  ☆29Updated 3 years ago
• zhuxinqimac / PS-SC
  Code for CVPR2021 paper 'Where and What? Examining Interpretable Disentangled Representations'.
  ☆44Updated 3 years ago
• VITA-Group / Once-for-All-Adversarial-Training
  [NeurIPS 2020] "Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free" by Haotao Wang*, Tianlong C…
  ☆44Updated 3 years ago
• MadryLab / spatial-pytorch
  Codebase for "Exploring the Landscape of Spatial Robustness" (ICML'19, https://arxiv.org/abs/1712.02779).
  ☆26Updated 5 years ago
• zhihengli-UR / discover_unknown_biases
  Official code of "Discover the Unknown Biased Attribute of an Image Classifier" (ICCV 2021)
  ☆20Updated 3 years ago
• mancinimassimiliano / pytorch_wbn
  PyTorch implementation of Weighted Batch-Normalization layers
  ☆37Updated 5 years ago
• HaohanWang / HEX
  Example implementation for the paper: (ICLR Oral) Learning Robust Representations by Projecting Superficial Statistics Out
  ☆27Updated 4 years ago
• Simon4Yan / Meta-set
  Automatic model evaluation (AutoEval) in CVPR'21&TPAMI'22
  ☆36Updated 2 years ago
• ermongroup / NDA
  ☆24Updated 3 years ago
• Muzammal-Naseer / SAT
  Official repository for "Stylized Adversarial Training" (TPAMI 2022)
  ☆11Updated 2 years ago
• cihangxie / SmoothAdversarialTraining
  Smooth Adversarial Training
  ☆68Updated 4 years ago
• srebuffi / lsd-clusters
  ☆46Updated 2 years ago
• youjiangxu / FaMUS
  ☆28Updated 3 years ago
• jhjacobsen / fully-invertible-revnet
  ☆31Updated 4 years ago
• liuchen11 / AdversaryLossLandscape
  On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]
  ☆36Updated 4 years ago
• Phoenix1153 / ViT_OOD_generalization
  ☆85Updated 3 years ago
• abietti / kernel_reg
  Pytorch implementation of regularization methods for deep networks obtained via kernel methods.
  ☆22Updated 5 years ago
• MadryLab / backgrounds_challenge
  ☆141Updated 4 years ago
• bfshi / InfoDrop
  Code for our paper "Informative Dropout for Robust Representation Learning: A Shape-bias Perspective" (ICML 2020)
  ☆125Updated 2 years ago