Alternatives and similar repositories for BAR

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

• alinlab / LfF
  Learning from Failure: Training Debiased Classifier from Biased Classifier (NeurIPS 2020)
  ☆94Updated 5 years ago
• MadryLab / backgrounds_challenge
  ☆143Updated 5 years ago
• princetonvisualai / DomainBiasMitigation
  ☆72Updated 5 years ago
• PolinaKirichenko / deep_feature_reweighting
  ☆111Updated 2 years ago
• singlasahil14 / salient_imagenet
  Code for the ICLR 2022 paper. Salient Imagenet: How to discover spurious features in deep learning?
  ☆41Updated 3 years ago
• Weixin-Liang / MetaShift
  MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts (ICLR 2022)
  ☆108Updated 3 years ago
• modestyachts / imagenet-testbed
  ImageNet Testbed, associated with the paper "Measuring Robustness to Natural Distribution Shifts in Image Classification."
  ☆119Updated 2 years ago
• JeanKaddour / WASAM
  Weight-Averaged Sharpness-Aware Minimization (NeurIPS 2022)
  ☆28Updated 3 years ago
• yoonholee / DivDis
  ☆39Updated 3 years ago
• feidfoe / learning-not-to-learn
  [CVPR2019]Learning Not to Learn : An adversarial method to train deep neural networks with biased data
  ☆112Updated 5 years ago
• EIDOSLAB / entangling-disentangling-bias
  EnD: Entangling and Disentangling deep representations for bias correction | CVPR21 https://doi.org/10.1109/CVPR46437.2021.01330
  ☆16Updated 4 years ago
• deeplearning-wisc / gradnorm_ood
  On the Importance of Gradients for Detecting Distributional Shifts in the Wild
  ☆56Updated 3 years ago
• YugeTen / fish
  Official implementation of paper Gradient Matching for Domain Generalization
  ☆124Updated 4 years ago
• clovaai / rebias
  Official Pytorch implementation of ReBias (Learning De-biased Representations with Biased Representations), ICML 2020
  ☆175Updated last year
• MadryLab / BREEDS-Benchmarks
  ☆56Updated 5 years ago
• anniesch / jtt
  Code for "Just Train Twice: Improving Group Robustness without Training Group Information"
  ☆73Updated last year
• erobic / bias-mitigators
  Demonstrates failures of bias mitigation methods under varying types/levels of biases (WACV 2021)
  ☆26Updated last year
• deeplearning-wisc / Spurious_OOD
  ☆23Updated 3 years ago
• facebookresearch / Whac-A-Mole
  Code for the paper "A Whac-A-Mole Dilemma Shortcuts Come in Multiples Where Mitigating One Amplifies Others"
  ☆51Updated last year
• harshays / simplicitybiaspitfalls
  The Pitfalls of Simplicity Bias in Neural Networks [NeurIPS 2020] (http://arxiv.org/abs/2006.07710v2)
  ☆42Updated 2 years ago
• dteney / collages-dataset
  ☆15Updated 3 years ago
• deeplearning-wisc / vit-spurious-robustness
  ☆27Updated 2 years ago
• VITA-Group / Adversarial-Contrastive-Learning
  [NeurIPS 2020] “ Robust Pre-Training by Adversarial Contrastive Learning”, Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangyang Wang
  ☆116Updated 4 years ago
• tml-epfl / adv-training-corruptions
  On the effectiveness of adversarial training against common corruptions [UAI 2022]
  ☆30Updated 3 years ago
• PotatoTian / TPGM
  This repo implements the CVPR23 paper Trainable Projected Gradient Method for Robust Fine-tuning
  ☆24Updated 2 years ago
• hendrycks / pre-training
  Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)
  ☆100Updated 3 years ago
• mbaradad / learning_with_noise
  Learning to See by Looking at Noise
  ☆113Updated last year
• aliasgharkhani / Masktune
  ☆29Updated 3 years ago
• alinlab / consistency-adversarial
  Consistency Regularization for Adversarial Robustness (AAAI 2022)
  ☆53Updated 4 years ago
• MadryLab / dataset-interfaces
  Dataset Interfaces: Diagnosing Model Failures Using Controllable Counterfactual Generation
  ☆45Updated 2 years ago