awesome-automl-papers
A curated list of automated machine learning papers and resources.
GraphCanon updated Oct 4, 2026 · GitHub synced Oct 4, 2026
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Decision brief
awesome-automl-papers is an organized collection of AutoML academic resources including papers on automated feature engineering, hyperparameter optimization, and neural architecture search.
Good fit when
- When you need a curated list of academic materials to research or learn about AutoML technologies
- To access recent developments in automating machine learning processes like feature engineering, model selection, and hyperparameter tuning
Avoid when
- If looking for direct integration with commercial AutoML systems, as the tool provides only a list of academic papers and resources
- When seeking practical AutoML solutions to directly apply in production settings without extensive customization or interpretation from papers
Observed Jul 15, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (844d since push)
- As of Oct 4, 2026
- Provenance
- Not a fork · Personal account
- As of Oct 4, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/hibayesian/awesome-automl-papersSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Provides access to AutoML-related academic material including papers on topics like automated feature engineering, hyperparameter optimization, and neural architecture search.
Capability facts
No sourced capability facts yet. Facts appear after ingest scans repo manifests (Dockerfile, package.json, MCP configs).
Categories
Tags
README
Awesome AutoML Papers Awesome AutoML Papers is a curated list of automated machine learning papers, articles, tutorials, slides and projects. Star this repository, and then you can keep abreast of the latest developments of this booming research field. Thanks to all the people wh...
For agents
This page has a .md twin and JSON over the API.