# markdtw/awesome-architecture-search

A curated list of awesome architecture search resources

Repository: https://github.com/markdtw/awesome-architecture-search
Canonical: https://ross.abutalabs.com/products/awesome-architecture-search
License Family: other
Topics: deep-learning, neural-architecture-search
Last push: 2020-09-15T19:52:12+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3201, "days_push": 2178, "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 1190, forks 198 (observed 2026-08-28T04:03:55.854228+00:00)

## What it is
A curated awesome-list of neural architecture search and hyper-parameter optimization resources, including papers and code links organized by technique such as reinforcement learning and evolutionary algorithms. It serves as a reference index rather than runnable software.

## Use cases
- find papers on neural architecture search
- learn about NAS with reinforcement learning
- discover hyper-parameter optimization resources
- find ENAS and NASNet implementations
- survey evolutionary algorithm approaches to architecture search
- get started with automated neural network design

## When to choose
- you need a reading list of NAS papers and code
- you are researching automated neural architecture design
- you want a quick overview of hyper-parameter optimization methods

## When to avoid
- you need a runnable NAS tool or library
- you need actively maintained resources after 2020
- you want tutorials rather than paper links

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, deep-learning
- domain: machine-learning, deep-learning, awesome-lists, tutorials
- platform: -
- tags: awesome-list, neural-architecture-search, hyperparameter-optimization, curated-resources, papers

## Member repositories
- markdtw/awesome-architecture-search (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:55.854228+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 2026-08-30T06:23:04.793834+00:00, confidence not recorded.
  - readme: https://github.com/markdtw/awesome-architecture-search (fetched 2026-08-28T04:03:55.854228+00:00, sha 42076c72627c)
- Data as of 2026-08-30T08:39:29.467469+00:00.