asappresearch / aum

Related projects: ⓘ

• AlanChou / Truncated-Loss
  PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018
  ☆123Updated 4 years ago
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  Official implementation of "Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning"
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• shamangary / Pytorch-Stochastic-Depth-Resnet
  Pytorch Implementation of Deep Networks with Stochastic Depth
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• chenpf1025 / noisy_label_understanding_utilizing
  ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
  ☆90Updated 3 years ago
• LiJunnan1992 / MLNT
  Meta-Learning based Noise-Tolerant Training
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  [ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels
  ☆132Updated 2 months ago
• snu-mllab / Co-Mixup
  Official PyTorch implementation of "Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity" (ICLR'21 Oral)
  ☆105Updated 2 years ago
• stanford-futuredata / selection-via-proxy
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• alinlab / Confident_classifier
  Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018
  ☆178Updated 4 years ago
• xingruiyu / coteaching_plus
  ICML'19 How does Disagreement Help Generalization against Label Corruption?
  ☆82Updated 5 years ago
• haochenglouis / cores
  Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)
  ☆34Updated 3 years ago
• perrying / pytorch-consistency-regularization
  PyTorch implementation of consistency regularization methods for semi-supervised learning
  ☆76Updated 4 years ago
• PaulAlbert31 / LabelNoiseCorrection
  Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction
  ☆219Updated 4 years ago
• UMBCvision / CompRess
  Compressing Representations for Self-Supervised Learning
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• vfdev-5 / UDA-pytorch
  Unsupervised Data Augmentation experiments in PyTorch
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  Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"
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  Unofficial PyTorch Implementation of Unsupervised Data Augmentation.
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• hankook / SLA
  Self-supervised Label Augmentation via Input Transformations (ICML 2020)
  ☆103Updated 3 years ago
• seominseok0429 / label-smoothing-visualization-pytorch
  When Does Label Smoothing Help?_pytorch_implementationimp
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• vcl-iisc / ZSKD
  Zero-Shot Knowledge Distillation in Deep Networks
  ☆64Updated 2 years ago
• jizongFox / pytorch-randaugment
  Unofficial PyTorch Reimplementation of AutoAugment and RandAugment.
  ☆36Updated 2 years ago
• yikun2019 / PENCIL
  PyTorch implementation of Probabilistic End-to-end Noise Correction for Learning with Noisy Labels, CVPR 2019.
  ☆138Updated 5 years ago
• ContrastToDivide / C2D
  PyTorch implementation of "Contrast to Divide: self-supervised pre-training for learning with noisy labels"
  ☆68Updated 3 years ago
• stanford-futuredata / sinkhorn-label-allocation
  Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in fu…
  ☆53Updated 3 years ago
• LeeDoYup / FixMatch-pytorch
  Unofficial Pytorch code for "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence" in NeurIPS'20. This repo co…
  ☆190Updated 3 years ago
• chingyaoc / DCL
  NeurIPS 2020, Debiased Contrastive Learning
  ☆281Updated last year
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  Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"
  ☆48Updated 2 years ago