Alternatives and similar repositories for Part-dependent-label-noise

Users that are interested in Part-dependent-label-noise are comparing it to the libraries listed below

• xiaoboxia / CDR
  ICLR‘2021: Robust Early-learning: Hindering the Memorization of Noisy Labels
  ☆77Updated 4 years ago
• xiaoboxia / T-Revision
  NeurIPS'2019: Are Anchor Points Really Indispensable in Label-Noise Learning?
  ☆100Updated 3 years ago
• xiaoboxia / Classification-with-noisy-labels-by-importance-reweighting
  TPAMI: Classification with noisy labels by importance reweighting.
  ☆40Updated 5 years ago
• ShuoYang-1998 / BLTM
  [ICML'2022] Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network
  ☆20Updated 3 years ago
• ZhenWang-PhD / Training-Noise-Robust-Deep-Neural-Networks-via-Meta-Learning
  Code for CVPR2020 ‘Training Noise Robust Deep Neural Networks via Meta-Learning’
  ☆20Updated 4 years ago
• ShikunLi / Sel-CL
  CVPR 2022: Selective-Supervised Contrastive Learning with Noisy Labels
  ☆93Updated 3 years ago
• lijichang / LNL-NCE
  A pytorch implementation for "Neighborhood Collective Estimation for Noisy Label Identification and Correction", which is accepted by ECC…
  ☆25Updated 2 years ago
• deeplearning-wisc / react
  Code for NeurIPS 2021 paper "ReAct: Out-of-distribution Detection With Rectified Activations"
  ☆53Updated 3 years ago
• tmllab / 2021_NeurIPS_PES
  ☆30Updated 2 years ago
• UCSC-REAL / cores
  Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)
  ☆38Updated 4 years ago
• haochenglouis / cores
  Learning with Instance-Dependent Label Noise: A Sample Sieve Approach (ICLR2021)
  ☆34Updated 4 years ago
• kaiwang960112 / CAFE
  This is a method of dataset condensation, and it has been accepted by CVPR-2022.
  ☆71Updated last year
• KaihuaTang / Generalized-Long-Tailed-Benchmarks.pytorch
  [ECCV 2022] A generalized long-tailed challenge that incorporates both the conventional class-wise imbalance and the overlooked attribute…
  ☆126Updated 11 months ago
• LAMDA-CL / Awesome-open-world-learning
  Awesome-open-world-learning
  ☆26Updated 3 years ago
• wutong16 / Adversarial_Long-Tail
  [ CVPR 2021 Oral ] Pytorch implementation for "Adversarial Robustness under Long-Tailed Distribution"
  ☆102Updated 4 years ago
• x-zho14 / MAPLE
  Code for Model Agnostic Sample Reweighting for Out-of-Distribution Learning
  ☆44Updated 2 years ago
• Vanint / SADE-AgnosticLT
  This repository is the official Pytorch implementation of Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Re…
  ☆162Updated 2 years ago
• shengliu66 / SOP
  Official Implementation of Robust Training under Label Noise by Over-parameterization
  ☆64Updated 2 years ago
• Kthyeon / FINE_official
  NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"
  ☆39Updated 3 years ago
• deeplearning-wisc / poem
  PyTorch implementation of POEM (Out-of-distribution detection with posterior sampling), ICML 2022
  ☆28Updated 2 years ago
• tmllab / 2021_ICCV_Me-Momentum
  ☆14Updated 2 years ago
• dvlab-research / MiSLAS
  Improving Calibration for Long-Tailed Recognition (CVPR2021)
  ☆148Updated 3 years ago
• justincui03 / dc_benchmark
  ☆86Updated 2 years ago
• youjiangxu / FaMUS
  ☆28Updated 3 years ago
• nazmul-karim170 / UNICON
  [CVPR'22] Official Implementation of the CVPR 2022 paper "UNICON: Combating Label Noise Through Uniform Selection and Contrastive Learnin…
  ☆62Updated 9 months ago
• QizhouWang / DOE
  ☆26Updated 2 years ago
• pxiangwu / PLC
  ICLR 2021, "Learning with feature-dependent label noise: a progressive approach"
  ☆43Updated 2 years ago
• takashiishida / comp
  [NeurIPS 2017] [ICML 2019] Code for complementary-label learning
  ☆49Updated last year
• snap-stanford / orca
  [ICLR 2022] Open-World Semi-Supervised Learning
  ☆101Updated 3 years ago
• xiaoboxia / CoDis
  ICCV'2023: Combating Noisy Labels with Sample Selection by Mining High-Discrepancy Examples
  ☆11Updated last year