Alternatives and similar repositories for loss-correction

Users that are interested in loss-correction are comparing it to the libraries listed below

• mmazeika / glc
  Gold Loss Correction
  ☆87Updated 6 years ago
• Cysu / noisy_label
  Code for the CVPR15 paper "Learning from Massive Noisy Labeled Data for Image Classification"
  ☆119Updated 6 years ago
• ShiyuLiang / odin-pytorch
  Principled Detection of Out-of-Distribution Examples in Neural Networks
  ☆202Updated 8 years ago
• 9310gaurav / virtual-adversarial-training
  Pytorch implementation of Virtual Adversarial Training
  ☆134Updated 6 years ago
• alinlab / Confident_classifier
  Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018
  ☆182Updated 5 years ago
• RuiShu / dirt-t
  A DIRT-T Approach to Unsupervised Domain Adaptation (ICLR 2018)
  ☆176Updated 7 years ago
• udibr / noisy_labels
  TRAINING DEEP NEURAL-NETWORKS USING A NOISE ADAPTATION LAYER
  ☆118Updated 8 years ago
• xingjunm / dimensionality-driven-learning
  Code for paper "Dimensionality-Driven Learning with Noisy Labels" - ICML 2018
  ☆58Updated last year
• s-laine / tempens
  Temporal ensembling for semi-supervised learning
  ☆159Updated 8 years ago
• benathi / fastswa-semi-sup
  Improving Consistency-Based Semi-Supervised Learning with Weight Averaging
  ☆186Updated 6 years ago
• ricvolpi / generalize-unseen-domains
  Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018
  ☆121Updated 5 years ago
• takerum / vat_tf
  Virtual adversarial training with Tensorflow
  ☆253Updated 7 years ago
• ashafaei / OD-test
  OD-test: A Less Biased Evaluation of Out-of-Distribution (Outlier) Detectors (PyTorch)
  ☆62Updated last year
• vikasverma1077 / ICT
  Code for reproducing ICT (published in Neural Networks 2022, and in IJCAI 2019)
  ☆149Updated 2 years ago
• danieltan07 / learning-to-reweight-examples
  PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning
  ☆354Updated 6 years ago
• uber-research / learning-to-reweight-examples
  Code for paper "Learning to Reweight Examples for Robust Deep Learning"
  ☆269Updated 6 years ago
• salesforce / corr_based_prediction
  This repo provides code used in the paper "Predicting with High Correlation Features" (https://arxiv.org/abs/1910.00164):
  ☆54Updated 3 months ago
• chenpf1025 / noisy_label_understanding_utilizing
  ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
  ☆91Updated 4 years ago
• hendrycks / error-detection
  A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
  ☆231Updated 6 years ago
• yulongwang12 / visual-attribution
  Pytorch Implementation of recent visual attribution methods for model interpretability
  ☆146Updated 5 years ago
• yogeshbalaji / Meta-Learning-Domain-Generalization
  ☆30Updated 7 years ago
• pluskid / fitting-random-labels
  Example code for the paper "Understanding deep learning requires rethinking generalization"
  ☆178Updated 5 years ago
• takerum / vat_chainer
  Implementation of Virtual adversarial training with chainer
  ☆40Updated 7 years ago
• LiJunnan1992 / MLNT
  Meta-Learning based Noise-Tolerant Training
  ☆126Updated 5 years ago
• thuml / Transferable-Adversarial-Training
  Code release for Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers (ICML2019)
  ☆81Updated 6 years ago
• Newbeeer / L_DMI
  Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"
  ☆119Updated 2 years ago
• OctoberChang / MMD-GAN
  MMD-GAN: Towards Deeper Understanding of Moment Matching Network
  ☆201Updated 2 years ago
• kylehkhsu / cactus-maml
  Code for Unsupervised Learning via Meta-Learning.
  ☆122Updated 6 years ago
• google-research / remixmatch
  ☆129Updated 2 years ago
• sungraepark / Adversarial-Dropout
  ☆32Updated 6 years ago