CleanlabThe standard package for machine learning with noisy labels, finding mislabeled data, and uncertainty quantification. Works with most datasets and models.
SnorkelA system for quickly generating training data with weak supervision
WeFEND-AAAI20Dataset for paper "Weak Supervision for Fake News Detection via Reinforcement Learning" published in AAAI'2020.
weak-supervision-for-NERFramework to learn Named Entity Recognition models without labelled data using weak supervision.
ASTRASelf-training with Weak Supervision (NAACL 2021)
spearSPEAR: Programmatically label and build training data quickly.
knodleA PyTorch-based open-source framework that provides methods for improving the weakly annotated data and allows researchers to efficiently develop and compare their own methods.
hamnetPyTorch implementation of AAAI 2021 paper: A Hybrid Attention Mechanism for Weakly-Supervised Temporal Action Localization
troveWeakly supervised medical named entity classification
weaselWeakly Supervised End-to-End Learning (NeurIPS 2021)
Learning-From-RulesImplementation of experiments in paper "Learning from Rules Generalizing Labeled Exemplars" to appear in ICLR2020 (https://openreview.net/forum?id=SkeuexBtDr)
concept-based-xaiLibrary implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI
wrenchWRENCH: Weak supeRvision bENCHmark