Alternatives and similar repositories for BREEDS-Benchmarks

Users that are interested in BREEDS-Benchmarks are comparing it to the libraries listed below

• ssagawa / overparam_spur_corr
  An Investigation of Why Overparameterization Exacerbates Spurious Correlations
  ☆31Updated 5 years ago
• bethgelab / InDomainGeneralizationBenchmark
  ☆34Updated 3 years ago
• wronnyhuang / gen-viz
  Code for the paper "Understanding Generalization through Visualizations"
  ☆61Updated 4 years ago
• MadryLab / DebuggableDeepNetworks
  ☆38Updated 4 years ago
• harshays / simplicitybiaspitfalls
  The Pitfalls of Simplicity Bias in Neural Networks [NeurIPS 2020] (http://arxiv.org/abs/2006.07710v2)
  ☆41Updated last year
• google-research / heldout-influence-estimation
  ☆62Updated 4 years ago
• mpezeshki / Gradient_Starvation
  Gradient Starvation: A Learning Proclivity in Neural Networks
  ☆61Updated 4 years ago
• tml-epfl / understanding-sam
  Towards Understanding Sharpness-Aware Minimization [ICML 2022]
  ☆35Updated 3 years ago
• facebookresearch / BalancingGroups
  Simple data balancing baselines for worst-group-accuracy benchmarks.
  ☆42Updated last year
• singlasahil14 / salient_imagenet
  Code for the ICLR 2022 paper. Salient Imagenet: How to discover spurious features in deep learning?
  ☆40Updated 3 years ago
• PolinaKirichenko / deep_feature_reweighting
  ☆108Updated last year
• JonasGeiping / fullbatchtraining
  Training vision models with full-batch gradient descent and regularization
  ☆37Updated 2 years ago
• ryoungj / optdom
  [ICLR'22] Self-supervised learning optimally robust representations for domain shift.
  ☆24Updated 3 years ago
• harshays / inputgradients
  Do input gradients highlight discriminative features? [NeurIPS 2021] (https://arxiv.org/abs/2102.12781)
  ☆13Updated 2 years ago
• anniesch / jtt
  Code for "Just Train Twice: Improving Group Robustness without Training Group Information"
  ☆72Updated last year
• izmailovpavel / spurious_feature_learning
  ☆46Updated 2 years ago
• Faruk-Ahmed / predictive_group_invariance
  ☆34Updated 4 years ago
• yaodongyu / Rethink-BiasVariance-Tradeoff
  Rethinking Bias-Variance Trade-off for Generalization of Neural Networks
  ☆49Updated 4 years ago
• yangarbiter / robust-local-lipschitz
  A Closer Look at Accuracy vs. Robustness
  ☆88Updated 4 years ago
• hendrycks / pre-training
  Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)
  ☆100Updated 3 years ago
• gibipara92 / learning-explanations-hard-to-vary
  Code to implement the AND-mask and geometric mean to do gradient based optimization, from the paper "Learning explanations that are hard …
  ☆40Updated 4 years ago
• singlasahil14 / barlow
  Code for the CVPR 2021 paper: Understanding Failures of Deep Networks via Robust Feature Extraction
  ☆36Updated 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
• facebookresearch / InvarianceUnitTests
  Toy datasets to evaluate algorithms for domain generalization and invariance learning.
  ☆42Updated 3 years ago
• locuslab / perturbation_learning
  Learning perturbation sets for robust machine learning
  ☆65Updated 4 years ago
• tml-epfl / sharpness-vs-generalization
  A modern look at the relationship between sharpness and generalization [ICML 2023]
  ☆43Updated last year
• nitarshan / robust-generalization-measures
  Official code for "In Search of Robust Measures of Generalization" (NeurIPS 2020)
  ☆28Updated 4 years ago
• MadryLab / backgrounds_challenge
  ☆141Updated 4 years ago
• bneyshabur / generalization-bounds
  Computing various measures and generalization bounds on convolutional and fully connected networks
  ☆35Updated 6 years ago
• chingyaoc / fair-mixup
  ICLR 2021, Fair Mixup: Fairness via Interpolation
  ☆56Updated 3 years ago