Alternatives and similar repositories for hold-me-tight:

Users that are interested in hold-me-tight are comparing it to the libraries listed below

• pdejorge / N-FGSM
  Official repo for the paper "Make Some Noise: Reliable and Efficient Single-Step Adversarial Training" (https://arxiv.org/abs/2202.01181)
  ☆25Updated 2 years ago
• tml-epfl / adv-training-corruptions
  On the effectiveness of adversarial training against common corruptions [UAI 2022]
  ☆30Updated 2 years ago
• davidstutz / disentangling-robustness-generalization
  CVPR'19 experiments with (on-manifold) adversarial examples.
  ☆44Updated 5 years ago
• davidstutz / confidence-calibrated-adversarial-training
  Implementation of Confidence-Calibrated Adversarial Training (CCAT).
  ☆45Updated 4 years ago
• MadryLab / DebuggableDeepNetworks
  ☆38Updated 3 years ago
• BorealisAI / mma_training
  Code for the paper "MMA Training: Direct Input Space Margin Maximization through Adversarial Training"
  ☆34Updated 4 years ago
• amodas / PRIME-augmentations
  PRIME: A Few Primitives Can Boost Robustness to Common Corruptions
  ☆42Updated 2 years ago
• singlasahil14 / barlow
  Code for the CVPR 2021 paper: Understanding Failures of Deep Networks via Robust Feature Extraction
  ☆35Updated 2 years ago
• MadryLab / dataset-replication-analysis
  ☆25Updated 4 years ago
• locuslab / intermediate_robustness
  ☆16Updated 3 years ago
• harshays / inputgradients
  Do input gradients highlight discriminative features? [NeurIPS 2021] (https://arxiv.org/abs/2102.12781)
  ☆13Updated 2 years ago
• ftramer / MultiRobustness
  Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019
  ☆47Updated 2 years ago
• guyAmit / GLOD
  Github for the conference paper GLOD-Gaussian Likelihood OOD detector
  ☆16Updated 2 years ago
• jh-jeong / smoothmix
  Code for the paper "SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness" (NeurIPS 2021)
  ☆21Updated 2 years ago
• fra31 / robust-finetuning
  Code relative to "Adversarial robustness against multiple and single $l_p$-threat models via quick fine-tuning of robust classifiers"
  ☆18Updated 2 years ago
• cassidylaidlaw / perceptual-advex
  Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".
  ☆55Updated 3 years ago
• ShawnXYang / AT_HE
  ☆35Updated 4 years ago
• JonasGeiping / dataaugs
  ☆17Updated 2 years ago
• clustr-official-account / Rethinking-Clustering-for-Robustness
  This is the official implementation of ClusTR: Clustering Training for Robustness paper.
  ☆20Updated 3 years ago
• liuchen11 / AdversaryLossLandscape
  On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]
  ☆35Updated 3 years ago
• facebookresearch / fisher_information_loss
  This code reproduces the results of the paper, "Measuring Data Leakage in Machine-Learning Models with Fisher Information"
  ☆50Updated 3 years ago
• preetum / cifar5m
  CIFAR-5m dataset
  ☆38Updated 4 years ago
• hendrycks / pre-training
  Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)
  ☆100Updated 3 years ago
• deepgenerativeclassifier / DeepBayes
  Code release for the ICML 2019 paper "Are generative classifiers more robust to adversarial attacks?"
  ☆23Updated 5 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
• enyac-group / Renofeation
  ☆19Updated 3 years ago
• val-iisc / BPFC
  Towards Achieving Adversarial Robustness by Enforcing Feature Consistency Across Bit Planes
  ☆22Updated 4 years ago
• GT-RIPL / Geometric-Sensitivity-Decomposition
  ☆18Updated 3 years ago
• yangarbiter / robust-local-lipschitz
  A Closer Look at Accuracy vs. Robustness
  ☆88Updated 3 years ago