Alternatives and similar repositories for AdjustBnd4Imbalance

Users that are interested in AdjustBnd4Imbalance are comparing it to the libraries listed below

• hankook / SLA
  Self-supervised Label Augmentation via Input Transformations (ICML 2020)
  ☆107Updated 5 years ago
• brjathu / SKD
  SKD : Self-supervised Knowledge Distillation for Few-shot Learning
  ☆102Updated 2 years ago
• valencebond / FixMatch_pytorch
  Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"
  ☆48Updated 3 years ago
• thuml / CoTuning
  Code release for NeurIPS 2020 paper "Co-Tuning for Transfer Learning"
  ☆40Updated 3 years ago
• snu-mllab / Co-Mixup
  Official PyTorch implementation of "Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity" (ICLR'21 Oral)
  ☆105Updated 4 years ago
• dvlab-research / MiSLAS
  Improving Calibration for Long-Tailed Recognition (CVPR2021)
  ☆153Updated 4 years ago
• alinlab / M2m
  Code for the paper "M2m: Imbalanced Classification via Major-to-minor Translation" (CVPR 2020)
  ☆95Updated 4 years ago
• xingruiyu / coteaching_plus
  ICML'19 How does Disagreement Help Generalization against Label Corruption?
  ☆90Updated 6 years ago
• szq0214 / Un-Mix
  Un-Mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning.
  ☆151Updated 3 years ago
• dvirsamuel / DRO-LT
  Code for our paper: Samuel and Chechik, "Distributional Robustness Loss for Long-tail Learning"
  ☆32Updated 3 years ago
• salesforce / MoPro
  MoPro: Webly Supervised Learning
  ☆88Updated 7 months ago
• yueatsprograms / uda_release
  Unsupervised Domain Adaptation through Self-Supervision
  ☆79Updated 4 years ago
• Lee-Gihun / MixCo-Mixup-Contrast
  (NeurIPS 2020 Workshop on SSL) Official Implementation of "MixCo: Mix-up Contrastive Learning for Visual Representation"
  ☆58Updated 3 years ago
• mancinimassimiliano / pytorch_wbn
  PyTorch implementation of Weighted Batch-Normalization layers
  ☆37Updated 5 years ago
• hongxin001 / JoCoR
  CVPR'20: Combating Noisy Labels by Agreement: A Joint Training Method with Co-Regularization
  ☆127Updated 2 years ago
• thuml / TransNorm
  Code release for "Transferable Normalization: Towards Improving Transferability of Deep Neural Networks" (NeurIPS 2019)
  ☆79Updated 5 years ago
• CoinCheung / fixmatch-pytorch
  90%+ with 40 labels. please see the readme for details.
  ☆36Updated 5 years ago
• YU1ut / JointOptimization
  Code for 'Joint Optimization Framework for Learning with Noisy Labels'
  ☆39Updated 7 years ago
• abdullahjamal / Longtail_DA
  [CVPR 2020] Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective
  ☆24Updated 5 years ago
• ContrastToDivide / C2D
  PyTorch implementation of "Contrast to Divide: self-supervised pre-training for learning with noisy labels"
  ☆71Updated 4 years ago
• dvornikita / SUR
  Code for the paper "Selecting Relevant Features from a Universal Representation for Few-shot Classification"
  ☆41Updated 4 years ago
• WonderSeven / ULDA
  The official implementation of paper "Unsupervised Few-Shot Learning via Distribution Shift-based Augmentation"
  ☆26Updated 3 years ago
• VisionLearningGroup / visda21-dev
  ☆46Updated 4 years ago
• xialeiliu / Awesome-LongTailed-Recognition
  ☆95Updated 5 years ago
• AlanChou / Truncated-Loss
  PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018
  ☆130Updated 6 years ago
• YU1ut / Ensemble-of-Leave-out-Classifiers
  Code for "Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-out Classifiers"
  ☆27Updated 3 years ago
• HaohanWang / HEX
  Example implementation for the paper: (ICLR Oral) Learning Robust Representations by Projecting Superficial Statistics Out
  ☆27Updated 4 years ago
• VITA-Group / SDCLR
  [ICML 2021] “ Self-Damaging Contrastive Learning”, Ziyu Jiang, Tianlong Chen, Bobak Mortazavi, Zhangyang Wang
  ☆63Updated 3 years ago
• gyhui14 / spottune
  SpotTune: Transfer Learning through Adaptive Fine-tuning
  ☆91Updated 6 years ago
• AlanChou / Super-Loss
  PyTorch implementation of the paper "SuperLoss: A Generic Loss for Robust Curriculum Learning" in NIPS 2020.
  ☆29Updated 4 years ago