Alternatives and similar repositories for SAMMD

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

• columbia / Metric_Learning_Adversarial_Robustness
  Code for NeurIPS 2019 Paper
  ☆47Updated 5 years ago
• chihhuiho / CLAE
  Implementation of Contrastive Learning with Adversarial Examples
  ☆29Updated 4 years ago
• jfc43 / informative-outlier-mining
  We propose a theoretically motivated method, Adversarial Training with informative Outlier Mining (ATOM), which improves the robustness o…
  ☆57Updated 3 years ago
• HanshuYAN / CIFS
  CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection
  ☆20Updated 3 years ago
• eddardd / WBTransport
  (ICASSP'21/CVPR'21) Wasserstein Barycenter Transport
  ☆30Updated 2 years ago
• A-LinCui / DenoisingNet_Adversarial_Training
  PyTorch implementation of "Feature Denoising for Improving Adversarial Robustness" on CIFAR10.
  ☆35Updated 5 years ago
• hongw579 / AGKD-BML
  Codes for ICCV 2021 paper "AGKD-BML: Defense Against Adversarial Attack by Attention Guided Knowledge Distillation and Bi-directional Met…
  ☆12Updated 3 years ago
• neu-spiral / HBaR
  ☆22Updated 3 years ago
• AkhilanB / Proper-Interpretability
  Codes for reproducing the experimental results in "Proper Network Interpretability Helps Adversarial Robustness in Classification", publi…
  ☆13Updated 5 years ago
• P2333 / Reverse-Cross-Entropy
  Reverse Cross Entropy for Adversarial Detection (NeurIPS 2018)
  ☆45Updated 4 years ago
• dvlab-research / LBGAT
  Learnable Boundary Guided Adversarial Training (ICCV2021)
  ☆38Updated 7 months ago
• VectorInstitute / gram-ood-detection
  ☆46Updated 4 years ago
• VITA-Group / Adversarial-Contrastive-Learning
  [NeurIPS 2020] “ Robust Pre-Training by Adversarial Contrastive Learning”, Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang
  ☆114Updated 3 years ago
• P2333 / Max-Mahalanobis-Training
  Max Mahalanobis Training (ICML 2018 + ICLR 2020)
  ☆90Updated 4 years ago
• garyzhao / ME-ADA
  "Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness" (NeurIPS 2020).
  ☆51Updated 4 years ago
• tml-epfl / understanding-fast-adv-training
  Understanding and Improving Fast Adversarial Training [NeurIPS 2020]
  ☆95Updated 3 years ago
• P2333 / Adaptive-Diversity-Promoting
  Adversarial Defense for Ensemble Models (ICML 2019)
  ☆61Updated 4 years ago
• LijieFan / AdvCL
  [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”
  ☆48Updated 3 years ago
• m-Just / OoD-Bench
  ☆44Updated 3 months ago
• dtak / adversarial-robustness-public
  Code for AAAI 2018 accepted paper: "Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing the…
  ☆55Updated 2 years ago
• xuanqing94 / BayesianDefense
  Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network
  ☆62Updated 6 years ago
• goldblum / AdversarialQuerying
  A PyTorch implementation of the method found in "Adversarially Robust Few-Shot Learning: A Meta-Learning Approach"
  ☆49Updated 4 years ago
• PKUAI26 / AT-CNN
  Project page for our paper: Interpreting Adversarially Trained Convolutional Neural Networks
  ☆66Updated 5 years ago
• tuananhbui89 / Adversarial-Divergence-Reduction
  Tensorflow implementation for the ECCV20 paper "Improving Adversarial Robustness by Enforcing Local and Global Compactness"
  ☆15Updated 4 years ago
• deeplearning-wisc / gradnorm_ood
  On the Importance of Gradients for Detecting Distributional Shifts in the Wild
  ☆56Updated 2 years ago
• YU1ut / Ensemble-of-Leave-out-Classifiers
  Code for "Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-out Classifiers"
  ☆27Updated 3 years ago
• charlesjin / adversarial_regularization
  A method based on manifold regularization for training adversarially robust neural networks
  ☆9Updated 5 years ago
• P2333 / Mixup-Inference
  Further improve robustness of mixup-trained models in inference (ICLR 2020)
  ☆60Updated 5 years ago
• hendrycks / pre-training
  Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)
  ☆100Updated 3 years ago
• Mephisto405 / Unsupervised-Out-of-Distribution-Detection-by-Maximum-Classifier-Discrepancy
  Reproducing experimental results of OOD-by-MCD [Yu and Aizawa et al. ICCV 2019]
  ☆30Updated 5 years ago