Alternatives and similar repositories for LibAUC:

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

• shengliu66 / ELR
  Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels
  ☆295Updated last year
• wetliu / energy_ood
  ☆408Updated 3 years ago
• ivanpanshin / SupCon-Framework
  Implementation of Supervised Contrastive Learning with AMP, EMA, SWA, and many other tricks
  ☆168Updated 2 years ago
• salesforce / hierarchicalContrastiveLearning
  ☆153Updated 2 years ago
• kkirchheim / pytorch-ood
  👽 Out-of-Distribution Detection with PyTorch
  ☆282Updated 2 weeks ago
• avihu111 / TypiClust
  Active Learning on a Budget - Opposite Strategies Suit High and Low Budgets
  ☆88Updated 4 months ago
• songhwanjun / Awesome-Noisy-Labels
  A Survey
  ☆549Updated 2 years ago
• YyzHarry / SubpopBench
  [ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift
  ☆108Updated last year
• AndrewAtanov / simclr-pytorch
  PyTorch implementation of SimCLR: supports multi-GPU training and closely reproduces results
  ☆202Updated 10 months ago
• mansheej / data_diet
  ☆105Updated last year
• kaidic / LDAM-DRW
  [NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
  ☆662Updated 3 years ago
• Jingkang50 / OODSurvey
  The Official Repository for "Generalized OOD Detection: A Survey"
  ☆453Updated 2 years ago
• shengliu66 / SOP
  Official Implementation of Robust Training under Label Noise by Over-parameterization
  ☆64Updated 2 years ago
• Reza-Safdari / SimSiam-91.9-top1-acc-on-CIFAR10
  Pytorch implementation of the paper Exploring Simple Siamese Representation Learning.
  ☆73Updated 4 years ago
• LiJunnan1992 / DivideMix
  Code for paper: DivideMix: Learning with Noisy Labels as Semi-supervised Learning
  ☆551Updated 4 years ago
• mlfoundations / model-soups
  Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time
  ☆448Updated 7 months ago
• torrvision / focal_calibration
  Code for the paper "Calibrating Deep Neural Networks using Focal Loss"
  ☆160Updated last year
• nayeemrizve / ups
  "In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning" by Mamshad Nayeem Riz…
  ☆234Updated last year
• EFS-OpenSource / calibration-framework
  The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a …
  ☆354Updated 7 months ago
• Separius / SimCLRv2-Pytorch
  Pretrained SimCLRv2 models in Pytorch
  ☆105Updated 4 years ago
• Chumsy0725 / logit-adj-pytorch
  PyTorch implementation of the paper: Long-tail Learning via Logit Adjustment
  ☆102Updated 3 years ago
• sthalles / PyTorch-BYOL
  PyTorch implementation of Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning
  ☆487Updated 2 years ago
• bhanML / label-noise-papers
  An update-to-date list for papers related with label-noise representation learning is here.
  ☆90Updated 3 years ago
• YGZWQZD / LAMDA-SSL
  30 Semi-Supervised Learning Algorithms
  ☆201Updated 6 months ago
• Jonathan-Pearce / calibration-toolbox
  NumPy library for calibration metrics
  ☆69Updated 2 weeks ago
• mathiaszinnen / focal_loss_torch
  Simple pytorch implementation of focal loss
  ☆84Updated last year
• Stomach-ache / awesome-long-tail-learning
  ☆473Updated 5 months ago
• runopti / stg
  Python/R library for feature selection in neural nets. ("Feature selection using Stochastic Gates", ICML 2020)
  ☆107Updated 3 years ago
• bhanML / Co-teaching
  NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels
  ☆500Updated 3 years ago
• KevinMusgrave / pytorch-adapt
  Domain adaptation made easy. Fully featured, modular, and customizable.
  ☆368Updated 2 years ago