benedekrozemberczki/awesome-gradient-boosting-papers
A curated collection of gradient boosting research papers with code implementations from major ML conferences.
Not currently ranked — collecting fresh signals.
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This repository aggregates academic papers on gradient boosting and adaptive boosting algorithms from top machine learning venues including NeurIPS, ICML, and ICLR. It includes implementations and covers major frameworks like XGBoost, LightGBM, and CatBoost alongside foundational techniques such as AdaBoost, decision trees, and random forests.
Frequently asked
- What is benedekrozemberczki/awesome-gradient-boosting-papers?
- A curated collection of gradient boosting research papers with code implementations from major ML conferences.
- Is awesome-gradient-boosting-papers open source?
- Yes — benedekrozemberczki/awesome-gradient-boosting-papers is open source, released under the CC0-1.0 license.
- What language is awesome-gradient-boosting-papers written in?
- benedekrozemberczki/awesome-gradient-boosting-papers is primarily written in Python.
- How popular is awesome-gradient-boosting-papers?
- benedekrozemberczki/awesome-gradient-boosting-papers has 1.1k stars on GitHub.
- Where can I find awesome-gradient-boosting-papers?
- benedekrozemberczki/awesome-gradient-boosting-papers is on GitHub at https://github.com/benedekrozemberczki/awesome-gradient-boosting-papers.