Alternatives and similar repositories for Critical-Path-Pruning

Users that are interested in Critical-Path-Pruning are comparing it to the libraries listed below

• PKUAI26 / AT-CNN
  Project page for our paper: Interpreting Adversarially Trained Convolutional Neural Networks
  ☆66Updated 6 years ago
• P2333 / Mixup-Inference
  Further improve robustness of mixup-trained models in inference (ICLR 2020)
  ☆60Updated 5 years ago
• wutong16 / Adversarial_Long-Tail
  [ CVPR 2021 Oral ] Pytorch implementation for "Adversarial Robustness under Long-Tailed Distribution"
  ☆102Updated 4 years ago
• columbia / Metric_Learning_Adversarial_Robustness
  Code for NeurIPS 2019 Paper
  ☆48Updated 5 years ago
• tingxueronghua / pytorch-classification-advprop
  ☆108Updated 3 years ago
• P2333 / Adaptive-Diversity-Promoting
  Adversarial Defense for Ensemble Models (ICML 2019)
  ☆61Updated 5 years ago
• YyzHarry / ME-Net
  [ICML 2019] ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
  ☆54Updated last month
• a1600012888 / YOPO-You-Only-Propagate-Once
  Code for our nips19 paper: You Only Propagate Once: Accelerating Adversarial Training Via Maximal Principle
  ☆178Updated last year
• wanglouis49 / pytorch-adversarial_box
  PyTorch library for adversarial attack and training
  ☆145Updated 6 years ago
• gmh14 / RobNets
  [CVPR 2020] When NAS Meets Robustness: In Search of Robust Architectures against Adversarial Attacks
  ☆124Updated 5 years ago
• mtoneva / example_forgetting
  ☆178Updated last year
• 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
• HaohanWang / HFC
  Implementation for the paper (CVPR Oral): High Frequency Component Helps Explain the Generalization of Convolutional Neural Networks
  ☆242Updated 4 years ago
• elliothe / CVPR_2019_PNI
  pytorch implementation of Parametric Noise Injection for adversarial defense
  ☆45Updated 6 years ago
• KaidiXu / StrAttack
  StrAttack, ICLR 2019
  ☆33Updated 6 years ago
• garyzhao / ME-ADA
  "Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness" (NeurIPS 2020).
  ☆51Updated 5 years ago
• sunblaze-ucb / curriculum-adversarial-training-CAT
  ☆14Updated 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
• P2333 / Max-Mahalanobis-Training
  Max Mahalanobis Training (ICML 2018 + ICLR 2020)
  ☆90Updated 4 years ago
• goldblum / AdversarialQuerying
  A PyTorch implementation of the method found in "Adversarially Robust Few-Shot Learning: A Meta-Learning Approach"
  ☆50Updated 5 years ago
• bhheo / BSS_distillation
  Knowledge Distillation with Adversarial Samples Supporting Decision Boundary (AAAI 2019)
  ☆71Updated 6 years ago
• karandwivedi42 / adversarial
  Pytorch - Adversarial Training
  ☆26Updated 7 years ago
• dongyp13 / Adversarial-Distributional-Training
  Adversarial Distributional Training (NeurIPS 2020)
  ☆63Updated 4 years ago
• P2333 / Bag-of-Tricks-for-AT
  Empirical tricks for training robust models (ICLR 2021)
  ☆257Updated 2 years ago
• mahyarnajibi / FreeAdversarialTraining
  PyTorch Implementation of Adversarial Training for Free!
  ☆248Updated 4 years ago
• xjtushujun / meta-weight-net
  NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).
  ☆289Updated 3 years ago
• yaircarmon / semisup-adv
  Semisupervised learning for adversarial robustness https://arxiv.org/pdf/1905.13736.pdf
  ☆141Updated 5 years ago
• davidstutz / disentangling-robustness-generalization
  CVPR'19 experiments with (on-manifold) adversarial examples.
  ☆45Updated 5 years ago
• VITA-Group / Adv-SS-Pretraining
  [CVPR 2020] Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning
  ☆85Updated 3 years ago
• lorenmt / maxl
  The implementation of "Self-Supervised Generalisation with Meta Auxiliary Learning" [NeurIPS 2019].
  ☆176Updated 3 years ago