Home/Compare/caffe vs awesome-automl-papers

Comparison

caffe vs awesome-automl-papers

Verdict

Pick caffe when license: caffe is Other, awesome-automl-papers is Apache-2.0; pick awesome-automl-papers when license: awesome-automl-papers is Apache-2.0, caffe is Other.

Markdown twin · caffe alternatives · awesome-automl-papers alternatives

GraphCanon updated today

caffe logo

caffe

BVLC/caffe

35kpushed Jul 31, 2024
vs
awesome-automl-papers logo

awesome-automl-papers

hibayesian/awesome-automl-papers

4.2kpushed Jun 11, 2024

Trust & integrity

Signalcaffeawesome-automl-papers
Maintenance
Dormant (710d since push)
As of today · github_public_v1
Dormant (760d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Personal account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
No lockfile
As of today · none

Tagline

caffe
Caffe: a fast open framework for deep learning.
awesome-automl-papers
A curated list of automated machine learning papers, articles, tutorials, slides and projects

Stars

caffe
35k
awesome-automl-papers
4.2k

Forks

caffe
18k
awesome-automl-papers
680

Open issues

caffe
1.2k
awesome-automl-papers
2

Language

caffe
C++
awesome-automl-papers
-

Adopt for

caffe
-
awesome-automl-papers
-

Persona

caffe
-
awesome-automl-papers
-

Runtime

caffe
-
awesome-automl-papers
-

License

caffe
Other
awesome-automl-papers
Apache-2.0

Last pushed

caffe
Jul 31, 2024
awesome-automl-papers
Jun 11, 2024

Categories

caffe
Computer Vision, Vector Databases
awesome-automl-papers
Computer Vision, Vector Databases

Trust and health

Days since push

caffe
710d
awesome-automl-papers
760d

Open issues (now)

caffe
1.2k
awesome-automl-papers
2

Owner type

caffe
Organization
awesome-automl-papers
User

Full report

awesome-automl-papers
Trust report

Choose caffe if…

  • License: caffe is Other, awesome-automl-papers is Apache-2.0.
  • Tags unique to caffe: c++, deep-learning, machine-learning, vision.
  • More GitHub stars (35k vs 4.2k) - visibility, not fit.

When NOT to use caffe

  • Last GitHub push was 710 days ago (dormant maintenance, Jul 31, 2024). Validate activity before betting a new project on caffe.
  • Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

Choose awesome-automl-papers if…

  • License: awesome-automl-papers is Apache-2.0, caffe is Other.
  • Tags unique to awesome-automl-papers: automated-feature-engineering, automl, hyperparameter-optimization, neural-architecture-search.
  • Leaner open-issue backlog (2).

When NOT to use awesome-automl-papers

  • Last GitHub push was 760 days ago (dormant maintenance, Jun 11, 2024). Validate activity before betting a new project on awesome-automl-papers.
  • Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: caffe 35k · awesome-automl-papers 4.2k (synced Jul 11, 2026).

Common questions

What is the difference between caffe and awesome-automl-papers?
caffe: Caffe: a fast open framework for deep learning.. awesome-automl-papers: A curated list of automated machine learning papers, articles, tutorials, slides and projects. See the comparison table for live GitHub stats and shared categories.
When should I choose caffe over awesome-automl-papers?
Choose caffe over awesome-automl-papers when License: caffe is Other, awesome-automl-papers is Apache-2.0; Tags unique to caffe: c++, deep-learning, machine-learning, vision; More GitHub stars (35k vs 4.2k) - visibility, not fit.
When should I choose awesome-automl-papers over caffe?
Choose awesome-automl-papers over caffe when License: awesome-automl-papers is Apache-2.0, caffe is Other; Tags unique to awesome-automl-papers: automated-feature-engineering, automl, hyperparameter-optimization, neural-architecture-search; Leaner open-issue backlog (2).
When should I avoid caffe?
Last GitHub push was 710 days ago (dormant maintenance, Jul 31, 2024). Validate activity before betting a new project on caffe. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
When should I avoid awesome-automl-papers?
Last GitHub push was 760 days ago (dormant maintenance, Jun 11, 2024). Validate activity before betting a new project on awesome-automl-papers. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
Is caffe or awesome-automl-papers more popular on GitHub?
caffe has more GitHub stars (34,574 vs 4,152). Stars measure visibility, not whether either tool fits your constraints.
Are caffe and awesome-automl-papers open source?
Yes - both are open-source projects on GitHub (caffe: Other, awesome-automl-papers: Apache-2.0).
Where can I find alternatives to caffe or awesome-automl-papers?
GraphCanon lists graph-backed alternatives at caffe alternatives and awesome-automl-papers alternatives (caffe markdown twin, awesome-automl-papers markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, caffe or awesome-automl-papers?
caffe: Dormant. awesome-automl-papers: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for caffe and awesome-automl-papers?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: caffe trust report; awesome-automl-papers trust report.