How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
Cleanlab is a data-centric AI library and toolkit designed to improve machine learning model performance by detecting label errors and increasing overall dataset quality. It implements a confident learning framework that iteratively refines label noise estimates by comparing model predictions with estimated label probabilities to identify mislabeled examples. The project provides specialized utilities for active learning optimization, allowing for the selection of the most impactful examples for labeling or re-labeling. It also includes an outlier detection tool to identify atypical data poin
Elsa: Energy-based Learning forSemi-supervised Anomaly Detection Official PyTorch implementation of "Elsa: Energy-based Learning forSemi-supervised Anomaly Detection" (BMVC 2021) by Sungwon Han, Hyeonho Song, Seungeon Lee, Sungwon Park, Meeyoung Cha.
CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances (NeurIPS 2020)
The main features of alinlab/csi are: Image Classification, Out of Distribution Detection.
Open-source alternatives to alinlab/csi include: hendrycks/ss-ood — Self-Supervised Learning for OOD Detection (NeurIPS 2019). cleanlab/cleanlab — Cleanlab is a data-centric AI library and toolkit designed to improve machine learning model performance by detecting… archon159/elsa — Elsa: Energy-based Learning forSemi-supervised Anomaly Detection Official PyTorch implementation of "Elsa:… deeplearning-wisc/mood. demonzyj56/e3outlier — E3Outlier: Effective End-to-end Unsupervised Outlier Detection. amazon-research/crossnorm-selfnorm.
