# floodsung/Meta-Learning-Papers

Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning

Repository: https://github.com/floodsung/Meta-Learning-Papers
Canonical: https://ross.abutalabs.com/products/meta-learning-papers
License Family: other
Topics: deep-learning, meta-learning, one-shot-learning, learning-to-learn, few-shot-learning
Last push: 2018-11-26T04:33:02+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3405, "days_push": 2837, "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 2656, forks 473 (observed 2026-08-28T04:07:07.306374+00:00)

## What it is
A curated reading list of academic papers on meta-learning, learning to learn, one-shot learning, few-shot learning, and lifelong learning. It organizes foundational and modern research papers into categories for researchers studying the field.

## Use cases
- find papers on meta-learning
- learn about few-shot learning research
- get a reading list for learning to learn
- survey one-shot learning literature
- find foundational meta-learning papers for a literature review

## When to choose
- you need a curated bibliography of meta-learning research
- you are starting research in few-shot or one-shot learning
- you want historical papers on learning-to-learn

## When to avoid
- you need runnable code or implementations
- you want tutorials or beginner explanations rather than papers
- you need up-to-date coverage of recent research

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation
- domain: deep-learning, machine-learning, artificial-intelligence, tutorials
- platform: cross-platform
- tags: meta-learning, few-shot-learning, one-shot-learning, paper-list, awesome-list, research-papers

## Member repositories
- floodsung/Meta-Learning-Papers (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:07.306374+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 2026-08-30T02:18:28.932003+00:00, confidence not recorded.
  - readme: https://github.com/floodsung/Meta-Learning-Papers (fetched 2026-08-28T04:07:07.306374+00:00, sha 896264cb7572)
- Data as of 2026-08-30T08:39:29.467469+00:00.