#Noisy-labels

cleanlab

cleanlab

Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Renumics

awesome-open-data-centric-ai

Curated list of open source tooling for data-centric AI on unstructured data.

weijiaheng

Advances-in-Label-Noise-Learning

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

encord-team

encord-active

The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling.

UCSC-REAL

negative-label-smoothing

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

Kangningthu

ADELE

Adaptive Early-Learning Correction for Segmentation from Noisy Annotations (CVPR 2022 Oral)

zhangchbin

OnlineLabelSmoothing

The official code for the paper "Delving Deep into Label Smoothing", IEEE TIP 2021