# subeeshvasu/Awesome-Learning-with-Label-Noise

A curated list of resources for Learning with Noisy Labels

Repository: https://github.com/subeeshvasu/Awesome-Learning-with-Label-Noise
Canonical: https://ross.abutalabs.com/products/awesome-learning-with-label-noise
License Family: other
Topics: noisy-labels, label-noise, deep-neural-networks, noisy-data, unreliable-labels, robust-learning
Last push: 2025-05-03T11:47:41+00:00

## Health v2 (maintenance only)
Score: 41/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 19, release rhythm 35, longevity 100
- inputs: {"age_days": 2604, "days_push": 487, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2717, forks 354 (observed 2026-08-28T04:07:12.139367+00:00)

## What it is
A curated awesome-list of papers, code, and surveys on learning with noisy labels in deep neural networks. It aggregates research resources on training models with unreliable or incorrect training labels.

## Use cases
- find papers on learning with noisy labels
- research robust training with label noise
- find code implementations for noisy label methods
- survey the field of learning with unreliable labels
- get started with label noise research
- find surveys on noisy data in deep learning

## When to choose
- you need a comprehensive bibliography of label-noise research
- you want links to papers with accompanying code
- you are surveying robust learning under noisy annotations

## When to avoid
- you need a runnable library or tool for label noise
- you want production code rather than research references
- you need non-deep-learning noise handling methods

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, deep-learning
- domain: machine-learning, deep-learning, tutorials, awesome-lists
- platform: cross-platform
- tags: awesome-list, noisy-labels, label-noise, robust-learning, papers, curated-resources

## Member repositories
- subeeshvasu/Awesome-Learning-with-Label-Noise (main) score 41

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:12.139367+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:15:20.687492+00:00, confidence not recorded.
  - readme: https://github.com/subeeshvasu/Awesome-Learning-with-Label-Noise (fetched 2026-08-28T04:07:12.139367+00:00, sha 64d9c4001792)
- Data as of 2026-08-30T08:39:29.467469+00:00.