Alternatives and similar repositories for dataaugs

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

• tml-epfl / sharpness-vs-generalization
  A modern look at the relationship between sharpness and generalization [ICML 2023]
  ☆43Updated 2 years ago
• MadryLab / DebuggableDeepNetworks
  ☆38Updated 4 years ago
• MadryLab / BREEDS-Benchmarks
  ☆55Updated 5 years ago
• MadryLab / datamodels-data
  Data for "Datamodels: Predicting Predictions with Training Data"
  ☆97Updated 2 years ago
• alexrame / diwa
  DiWA: Diverse Weight Averaging for Out-of-Distribution Generalization
  ☆31Updated 2 years ago
• izmailovpavel / spurious_feature_learning
  ☆46Updated 2 years ago
• 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 3 years ago
• google-research / understanding-curricula
  ☆34Updated 6 months ago
• MadryLab / failure-directions
  Distilling Model Failures as Directions in Latent Space
  ☆47Updated 2 years ago
• nitarshan / robust-generalization-measures
  Official code for "In Search of Robust Measures of Generalization" (NeurIPS 2020)
  ☆28Updated 5 years ago
• tml-epfl / understanding-sam
  Towards Understanding Sharpness-Aware Minimization [ICML 2022]
  ☆37Updated 3 years ago
• joshr17 / IFM
  Code for paper "Can contrastive learning avoid shortcut solutions?" NeurIPS 2021.
  ☆47Updated 3 years ago
• MadryLab / modeldiff
  ModelDiff: A Framework for Comparing Learning Algorithms
  ☆58Updated 2 years ago
• locuslab / perturbation_learning
  Learning perturbation sets for robust machine learning
  ☆65Updated 4 years ago
• MadryLab / EditingClassifiers
  ☆96Updated 3 years ago
• singlasahil14 / barlow
  Code for the CVPR 2021 paper: Understanding Failures of Deep Networks via Robust Feature Extraction
  ☆36Updated 3 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"
  ☆19Updated 3 years ago
• js-d / sim_metric
  ☆37Updated 2 years ago
• LTS4 / hold-me-tight
  Source code of "Hold me tight! Influence of discriminative features on deep network boundaries"
  ☆21Updated 4 years ago
• JonasGeiping / fullbatchtraining
  Training vision models with full-batch gradient descent and regularization
  ☆39Updated 2 years ago
• harshays / inputgradients
  Do input gradients highlight discriminative features? [NeurIPS 2021] (https://arxiv.org/abs/2102.12781)
  ☆13Updated 2 years ago
• davidstutz / confidence-calibrated-adversarial-training
  Implementation of Confidence-Calibrated Adversarial Training (CCAT).
  ☆45Updated 5 years ago
• mueller-mp / SAM-ON
  ☆34Updated last year
• AllanYangZhou / generative-invariance-transfer
  ☆26Updated 3 years ago
• MadryLab / dataset-interfaces
  Dataset Interfaces: Diagnosing Model Failures Using Controllable Counterfactual Generation
  ☆45Updated 2 years ago
• MadryLab / smoothed-vit
  Certified Patch Robustness via Smoothed Vision Transformers
  ☆42Updated 4 years ago
• google-research / heldout-influence-estimation
  ☆62Updated 4 years ago
• modestyachts / cifar-10.2
  Host CIFAR-10.2 Data Set
  ☆13Updated 4 years ago
• mpezeshki / Gradient_Starvation
  Gradient Starvation: A Learning Proclivity in Neural Networks
  ☆61Updated 4 years ago
• r-three / mats
  ☆32Updated last year