Alternatives and similar repositories for Nested-Co-teaching

Users that are interested in Nested-Co-teaching are comparing it to the libraries listed below

• salesforce / CoMatch
  Code for CoMatch: Semi-supervised Learning with Contrastive Graph Regularization
  ☆128Updated 3 months ago
• dvlab-research / MiSLAS
  Improving Calibration for Long-Tailed Recognition (CVPR2021)
  ☆148Updated 3 years ago
• ContrastToDivide / C2D
  PyTorch implementation of "Contrast to Divide: self-supervised pre-training for learning with noisy labels"
  ☆71Updated 4 years ago
• youjiangxu / FaMUS
  ☆28Updated 3 years ago
• frank-xwang / debiased-pseudo-labeling
  [CVPR 2022] Pytorch implementation for “Debiased Learning from Naturally Imbalanced Pseudo-Labels”
  ☆99Updated 2 years ago
• KentoNishi / Augmentation-for-LNL
  [CVPR 2021] Code for "Augmentation Strategies for Learning with Noisy Labels".
  ☆112Updated 3 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
• chandar-lab / PatchUp
  ☆39Updated 2 years ago
• szq0214 / Un-Mix
  Un-Mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning.
  ☆151Updated 3 years ago
• brjathu / SKD
  SKD : Self-supervised Knowledge Distillation for Few-shot Learning
  ☆99Updated last year
• VisionLearningGroup / visda21-dev
  ☆46Updated 4 years ago
• linusericsson / ssl-transfer
  Official code for the CVPR 2021 paper "How Well Do Self-Supervised Models Transfer?"
  ☆185Updated last year
• alinlab / cs-kd
  Regularizing Class-wise Predictions via Self-knowledge Distillation (CVPR 2020)
  ☆108Updated 5 years ago
• liulu112601 / URT
  ICLR 2021: A Universal Representation Transformer Layer for Few-Shot Image Classification
  ☆105Updated 4 years ago
• by-liu / MbLS
  Code of our method MbLS (Margin-based Label Smoothing) for network calibration. To Appear at CVPR 2022. Paper : https://arxiv.org/abs/211…
  ☆50Updated 2 years ago
• snu-mllab / Co-Mixup
  Official PyTorch implementation of "Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity" (ICLR'21 Oral)
  ☆106Updated 3 years ago
• UMBCvision / MSF
  Official code for "Mean Shift for Self-Supervised Learning"
  ☆57Updated 3 years ago
• pxiangwu / PLC
  ICLR 2021, "Learning with feature-dependent label noise: a progressive approach"
  ☆43Updated 2 years ago
• hongxin001 / JoCoR
  CVPR'20: Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization
  ☆127Updated last year
• alinlab / M2m
  Code for the paper "M2m: Imbalanced Classification via Major-to-minor Translation" (CVPR 2020)
  ☆95Updated 3 years ago
• amazon-science / exponential-moving-average-normalization
  PyTorch implementation of EMAN for self-supervised and semi-supervised learning: https://arxiv.org/abs/2101.08482
  ☆103Updated 4 years ago
• NVlabs / CSG
  ☆28Updated 4 years ago
• Separius / SimCLRv2-Pytorch
  Pretrained SimCLRv2 models in Pytorch
  ☆105Updated 4 years ago
• deeplearning-wisc / large_scale_ood
  MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space
  ☆93Updated 4 years ago
• mboudiaf / TIM
  (NeurIPS 2020) Transductive Information Maximization for Few-Shot Learning https://arxiv.org/abs/2008.11297
  ☆122Updated 2 years ago
• HanxunH / Active-Passive-Losses
  [ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels
  ☆138Updated last year
• ErikEnglesson / GJS
  The official code for the NeurIPS 2021 paper Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels (https://arxiv.org…
  ☆23Updated 3 years ago
• BIT-DA / MetaSAug
  [CVPR 2021] MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition
  ☆61Updated 2 years ago
• arghosh / noisy_label_pretrain
  ☆32Updated 4 years ago
• frank-xwang / CLD-UnsupervisedLearning
  [CVPR 2021] Code release for "Unsupervised Feature Learning by Cross-Level Instance-Group Discrimination."
  ☆101Updated 3 years ago