Alternatives and similar repositories for AugMax:

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

• snu-mllab / Co-Mixup
  Official PyTorch implementation of "Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity" (ICLR'21 Oral)
  ☆103Updated 3 years ago
• facebookresearch / augmentation-corruption
  This repository provides code for "On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness".
  ☆45Updated 2 years ago
• megvii-research / FSSD_OoD_Detection
  [SafeAI'21] Feature Space Singularity for Out-of-Distribution Detection.
  ☆80Updated 4 years ago
• dydjw9 / Efficient_SAM
  ☆57Updated 2 years ago
• tingxueronghua / pytorch-classification-advprop
  ☆107Updated 3 years ago
• VITA-Group / CV_LTH_Pre-training
  [CVPR 2021] "The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models" Tianlong Chen, Jon…
  ☆68Updated 2 years ago
• amodas / PRIME-augmentations
  PRIME: A Few Primitives Can Boost Robustness to Common Corruptions
  ☆42Updated 2 years ago
• luoyan407 / congruency
  [TPAMI 2019] The implementation for "Direction Concentration Learning: Enhancing Congruency in Machine Learning"
  ☆23Updated 5 years ago
• dedeswim / vits-robustness-torch
  Code for the paper "A Light Recipe to Train Robust Vision Transformers" [SaTML 2023]
  ☆53Updated 2 years ago
• cihangxie / SmoothAdversarialTraining
  Smooth Adversarial Training
  ☆67Updated 4 years ago
• somepago / dbViz
  The official PyTorch implementation - Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from t…
  ☆77Updated 2 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 last year
• gatheluck / FourierHeatmap
  Unofficial pytorch implementation of Fourier Heat Map proposed in 'A Fourier Perspective on Model Robustness in Computer Vision' [Yin+, N…
  ☆73Updated 10 months ago
• MingSun-Tse / Smile-Pruning
  A generic code base for neural network pruning, especially for pruning at initialization.
  ☆30Updated 2 years ago
• deeplearning-wisc / gradnorm_ood
  On the Importance of Gradients for Detecting Distributional Shifts in the Wild
  ☆55Updated 2 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
• andyzoujm / pixmix
  PixMix: Dreamlike Pictures Comprehensively Improve Safety Measures (CVPR 2022)
  ☆105Updated 2 years ago
• MadryLab / backgrounds_challenge
  ☆140Updated 4 years ago
• meijieru / fast_advprop
  [ICLR 2022]: Fast AdvProp
  ☆34Updated 2 years ago
• jfc43 / robust-ood-detection
  Robust Out-of-distribution Detection in Neural Networks
  ☆72Updated 2 years ago
• hendrycks / imagenet-r
  ImageNet-R(endition) and DeepAugment (ICCV 2021)
  ☆261Updated 3 years ago
• amazon-science / normalizer-free-robust-training
  Official implementation of "Removing Batch Normalization Boosts Adversarial Training" (ICML'22)
  ☆19Updated 2 years ago
• Lee-Gihun / MixCo-Mixup-Contrast
  (NeurIPS 2020 Workshop on SSL) Official Implementation of "MixCo: Mix-up Contrastive Learning for Visual Representation"
  ☆58Updated 2 years ago
• da2so / Data-Free_Network_Quantization_With_Adversarial_Knowledge_Distillation
  Data-Free Network Quantization With Adversarial Knowledge Distillation PyTorch
  ☆29Updated 3 years ago
• pairlab / CBS
  Curriculum by Smoothing (NeurIPS 2020)
  ☆39Updated 4 years ago
• VITA-Group / Adv-SS-Pretraining
  [CVPR 2020] Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning
  ☆85Updated 3 years ago
• VectorInstitute / gram-ood-detection
  ☆46Updated 4 years ago
• deeplearning-wisc / dice
  Code for ECCV 2022 paper "DICE: Leveraging Sparsification for Out-of-Distribution Detection"
  ☆40Updated 2 years ago
• Phoenix1153 / ViT_OOD_generalization
  ☆84Updated 2 years ago
• LijieFan / AdvCL
  [NeurIPS 2021] “When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?”
  ☆48Updated 3 years ago