computorg/published-202402-lefort-peerannot

Peerannot: classification for crowdsourced image datasets with Python

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agr78/PRLx-GAN

Generative modeling and latent projection label denoising approach to create synthetic rim lesions on QSM

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lucidrains/GAF-microbatch-pytorch

Implementation of Gradient Agreement Filtering, from Chaubard et al. of Stanford, but for single machine microbatches, in Pytorch

Language: Python - Size: 146 KB - Last synced at: 22 days ago - Pushed at: 5 months ago - Stars: 25 - Forks: 0

Westlake-AI/SemiReward

[ICLR 2024] SemiReward: A General Reward Model for Semi-supervised Learning

Language: Python - Size: 1.13 MB - Last synced at: about 2 months ago - Pushed at: about 1 year ago - Stars: 66 - Forks: 2

subeeshvasu/Awesome-Learning-with-Label-Noise

A curated list of resources for Learning with Noisy Labels

Size: 400 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 2,680 - Forks: 354

biquality-learn/biquality-learn

A Python Library for Biquality Learning

Language: Python - Size: 132 KB - Last synced at: 14 days ago - Pushed at: 3 months ago - Stars: 14 - Forks: 1

KentoNishi/Augmentation-for-LNL

[CVPR 2021] Code for "Augmentation Strategies for Learning with Noisy Labels".

Language: Python - Size: 50.1 MB - Last synced at: 28 days ago - Pushed at: over 3 years ago - Stars: 113 - Forks: 12

chengtan9907/Co-learning

The official implementation of the ACM MM'21 paper Co-learning: Learning from noisy labels with self-supervision.

Language: Python - Size: 104 KB - Last synced at: about 2 months ago - Pushed at: about 3 years ago - Stars: 120 - Forks: 10

weijiaheng/Advances-in-Label-Noise-Learning

A curated (most recent) list of resources for Learning with Noisy Labels

Size: 528 KB - Last synced at: 3 months ago - Pushed at: 9 months ago - Stars: 684 - Forks: 62

UCSC-REAL/cifar-10-100n

Human annotated noisy labels for CIFAR-10 and CIFAR-100. The website of CIFAR-N is available at http://www.noisylabels.com/.

Language: Python - Size: 3.43 MB - Last synced at: 3 months ago - Pushed at: about 2 years ago - Stars: 172 - Forks: 21

YutingLi0606/SURE

“SURE: SUrvey REcipes for building reliable and robust deep networks” (CVPR 2024) & (ECCV 2024 OOD-CV Challenge Winner)

Language: Python - Size: 5.55 MB - Last synced at: 3 months ago - Pushed at: 8 months ago - Stars: 57 - Forks: 5

msesia/conformal-label-noise

This repository implements conformal prediction methods for classification tasks that can automatically adapt to random label contamination in the calibration sample.

Language: Python - Size: 133 KB - Last synced at: 3 months ago - Pushed at: about 1 year ago - Stars: 3 - Forks: 1

dhofmann34/Unity

Agree to Disagree: Robust Anomaly Detection with Noisy Labels (SIGMOD 2025)

Language: Jupyter Notebook - Size: 24.5 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 1 - Forks: 0

julilien/MitigatingLabelNoiseDataAmbiguation

Supplementary material and code for "Mitigating Label Noise through Data Ambiguation" as published at AAAI 2024.

Language: Python - Size: 882 KB - Last synced at: 3 months ago - Pushed at: about 1 year ago - Stars: 5 - Forks: 0

kiyoon/verb_ambiguity

Official implementation of "An Action Is Worth Multiple Words: Handling Ambiguity in Action Recognition", BMVC 2022

Language: Python - Size: 1.07 MB - Last synced at: 3 months ago - Pushed at: over 2 years ago - Stars: 12 - Forks: 0

kuanghuei/clean-net

Tensorflow source code for "CleanNet: Transfer Learning for Scalable Image Classifier Training with Label Noise" (CVPR 2018)

Language: Python - Size: 875 KB - Last synced at: 7 days ago - Pushed at: about 7 years ago - Stars: 88 - Forks: 26

zjfheart/BadLabels

Challenging label noise called BadLabel; Robust label-noise learning called Robust DivideMix

Language: Python - Size: 39.6 MB - Last synced at: 3 months ago - Pushed at: over 1 year ago - Stars: 12 - Forks: 0

glhr/ood-labelnoise

"A noisy elephant in the room: Is your out-of-distribution detector robust to label noise?" (CVPR 2024)

Language: Jupyter Notebook - Size: 29 MB - Last synced at: 3 months ago - Pushed at: 10 months ago - Stars: 9 - Forks: 0

lucidrains/GAF-linear

Explorations into Gradient Agreement Filtering, proposed by Chaubard et al. at Stanford University

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U-Alberta/KG-Type-Correction

Code and data for the WWW 2021 research-track paper: Typing Errors in Factual Knowledge Graphs: Severity and Possible Ways Out

Language: Python - Size: 46.9 KB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 6 - Forks: 1

KentoNishi/Aug-for-LNL-Extras

Extra bits of unsanitized code for plotting, training, etc. related to our CVPR 2021 paper "Augmentation Strategies for Learning with Noisy Labels".

Language: Jupyter Notebook - Size: 26.7 MB - Last synced at: 3 months ago - Pushed at: about 4 years ago - Stars: 7 - Forks: 0

eraseai/erase

[CIKM-2024] Official code for work "ERASE: Error-Resilient Representation Learning on Graphs for Label Noise Tolerance"

Language: Python - Size: 5.85 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 17 - Forks: 2

LayneH/self-adaptive-training

[TPAMI2022 & NeurIPS2020] Official implementation of Self-Adaptive Training

Language: Python - Size: 91.8 KB - Last synced at: 7 months ago - Pushed at: over 3 years ago - Stars: 127 - Forks: 23

sduzpf/ERAT

Effective and Robust Adversarial Training Against Data and Label Corruptions

Language: Python - Size: 36.1 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

pxiangwu/PLC

ICLR 2021, "Learning with feature-dependent label noise: a progressive approach"

Language: Python - Size: 1.25 MB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 41 - Forks: 8

HanxunH/Active-Passive-Losses

[ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels

Language: Python - Size: 4.76 MB - Last synced at: over 1 year ago - Pushed at: almost 5 years ago - Stars: 123 - Forks: 28

tmlr-group/RGIB Fork of AndrewZhou924/RGIB

[NeurIPS 2023] Combating Bilateral Edge Noise for Robust Link Prediction

Language: Python - Size: 843 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 3 - Forks: 0

AndrewZhou924/RGIB

[NeurIPS 2023] Combating Bilateral Edge Noise for Robust Link Prediction

Language: Python - Size: 843 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 1

josch14/double-descent

Double Descent results for FCNNs on MNIST, extended by Label Noise (Reconciling Modern Machine-Learning Practice and the Classical Bias–Variance Trade-Off).

Language: Python - Size: 1.81 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

arghosh/RobustMW-Net

Language: Python - Size: 13.7 KB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 7 - Forks: 3

dmizr/phuber

[Re] Can gradient clipping mitigate label noise? (ML Reproducibility Challenge 2020)

Language: Python - Size: 1.32 MB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 14 - Forks: 6

carlomarxdk/RobustCrossEntropyLoss

PyTorch Implementation of Robust Cross Entropy Loss (Loss Correction for Label Noise)

Language: Python - Size: 7.81 KB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0

mirkobunse/pkccn

Learning algorithms for partially-known class-conditional label noise

Language: TeX - Size: 993 KB - Last synced at: 12 days ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

XinshaoAmosWang/Improving-Mean-Absolute-Error-against-CCE

Mean Absolute Error Does Not Treat Examples Equally and Gradient Magnitude’s Variance Matters

Language: Shell - Size: 45.1 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 29 - Forks: 3

YujiaBao/ls

Learning to Split for Automatic Bias Detection

Language: Python - Size: 809 KB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 45 - Forks: 4

bupt-ai-cz/HSA-NRL

Hard Sample Aware Noise Robust Learning forHistopathology Image Classification

Language: Python - Size: 366 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 26 - Forks: 7

weijiaheng/Robust-f-divergence-measures

[ICLR2021] Official Pytorch implementation of "When Optimizing f-Divergence is Robust with Label noise"

Language: Python - Size: 82.7 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 80 - Forks: 21

UCSC-REAL/negative-label-smoothing

[ICML2022 Long Talk] Official Pytorch implementation of "To Smooth or Not? When Label Smoothing Meets Noisy Labels"

Language: Python - Size: 337 KB - Last synced at: over 2 years ago - Pushed at: almost 3 years ago - Stars: 73 - Forks: 9

Castel44/SREA

SREA: Self-Re-Labeling with Embedding Analysis

Language: Python - Size: 217 KB - Last synced at: over 2 years ago - Pushed at: almost 4 years ago - Stars: 5 - Forks: 0

chenpf1025/RobustnessAccuracy

AAAI 2021: Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels

Language: Python - Size: 22.7 MB - Last synced at: over 2 years ago - Pushed at: about 4 years ago - Stars: 20 - Forks: 2

olivesgatech/Ramifications-HLU

[NeurIPSW 2022] On the Ramifications of Human Label Uncertainty

Language: Python - Size: 3.26 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0

chenpf1025/IDN

AAAI 2021: Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise

Language: Python - Size: 13.6 MB - Last synced at: over 2 years ago - Pushed at: about 4 years ago - Stars: 26 - Forks: 8

kremerj/relabeling

Code repository for the robust active label correction paper.

Language: Terra - Size: 15.6 MB - Last synced at: 4 months ago - Pushed at: about 7 years ago - Stars: 10 - Forks: 2

fengliu90/Butterfly

This is the source code for Butterfly: One-step Approach towards Wildly Unsupervised Domain Adaptation (NeurIPS'19 Workshop).

Language: Python - Size: 39.1 KB - Last synced at: over 2 years ago - Pushed at: about 4 years ago - Stars: 3 - Forks: 0

mangye16/ReID-Label-Noise

Language: Python - Size: 3.21 MB - Last synced at: over 2 years ago - Pushed at: over 3 years ago - Stars: 16 - Forks: 6

XinshaoAmosWang/DerivativeManipulation

In the context of Deep Learning: What is the right way to conduct example weighting? How do you understand loss functions and so-called theorems on them?

Language: Shell - Size: 48.3 MB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 9 - Forks: 1

sayakpaul/Analytics-Vidhya-Game-of-Deep-Learning-Hackathon

Contains my experiments for the Game of Deep Learning Hackathon conducted by Analytics Vidhya

Language: Jupyter Notebook - Size: 83.9 MB - Last synced at: 7 days ago - Pushed at: about 6 years ago - Stars: 7 - Forks: 1

junxia97/Co-training-based_noisy-label-learning Fork of chengtan9907/Co-learning-Learning-from-noisy-labels-with-self-supervision

[ACM MM 2021 Oral Presentation] A unified framework for co-training-based noisy label learning methods.

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alexmirrington/class-conditional-label-noise

Implementations of different loss-correction techniques to help deep models learn under class-conditional label noise.

Language: Python - Size: 7.06 MB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

alejandrods/Analysis-of-classifiers-robust-to-noisy-labels

Analysis of robust classification algorithms for overcoming class-dependant labelling noise: Forward, Importance Reweighting and T-revision. We demonstrate methods for estimating the transition matrix in order to obtain better classifier performance when working with noisy data.

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nahian-ahmed/labeling-satellite-images

Language: JavaScript - Size: 155 KB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

aajanki/label-noise-classification

A small experiment on classification with noisy labels

Language: Jupyter Notebook - Size: 458 KB - Last synced at: 30 days ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0