The standard data-centric AI package for data quality and machine learni...
A curated list of resources for Learning with Noisy Labels
Curated list of open source tooling for data-centric AI on unstructured ...
A curated (most recent) list of resources for Learning with Noisy Labels
NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Wei...
Code for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Nois...
Noise-Tolerant Paradigm for Training Face Recognition CNNs [Official, CV...
[ICML2020] Normalized Loss Functions for Deep Learning with Noisy Labels
The official implementation of the ACM MM'2021 paper Co-learning: Learni...
NLNL: Negative Learning for Noisy Labels
ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with...
MoPro: Webly Supervised Learning
[ICLR2021] Official Pytorch implementation of "When Optimizing f-Diverge...
The official code for the paper "Delving Deep into Label Smoothing", IEE...
[NeurIPS 2020] Disentangling Human Error from the Ground Truth in Segmen...