# benedekrozemberczki/awesome-gradient-boosting-papers

A curated list of gradient boosting research papers with implementations.

Repository: https://github.com/benedekrozemberczki/awesome-gradient-boosting-papers
Canonical: https://ross.abutalabs.com/products/awesome-gradient-boosting-papers
Language: Python
License: CC0-1.0
License Family: permissive
Topics: gradient-boosting, gradient-boosting-classifier, gradient-boosting-machine, gradient-boosted-trees, gradient-boosting-decision-trees, xgboost, xgboost-algorithm, catboost, lightgbm, random-forest, decision-tree, classification-algorithm, classification-trees, machine-learning, deep-learning, h2o, classifier, classification-tree, adaboost, boosting
Last push: 2026-01-05T12:39:45+00:00

## Health v2 (maintenance only)
Score: 58/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 60, release rhythm 32, longevity 100
- inputs: {"age_days": 2671, "days_push": 240, "days_rel": 240, "gap_med": null, "n_releases_24m": 1}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1049, forks 167 (observed 2026-08-28T04:03:22.743746+00:00)

## What it is
A curated awesome-list of gradient and adaptive boosting research papers, each linked to paper sources and code implementations. It covers publications from major ML, CV, NLP, data mining, and AI conferences.

## Use cases
- find gradient boosting research papers with code
- learn about xgboost lightgbm catboost research
- keep up with new boosting papers from NeurIPS KDD
- find implementations of gradient boosted tree algorithms
- research adaboost and boosting ensemble methods
- find papers on pruning boosted tree ensembles

## When to choose
- you want a curated, organized-by-conference reading list of boosting papers with linked implementations
- you are researching gradient boosting or tree ensembles and need references

## When to avoid
- you need a runnable gradient boosting library rather than a paper list
- you want tutorials or courses instead of academic papers

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning
- domain: machine-learning, awesome-lists, tutorials
- platform: python
- tags: gradient-boosting, xgboost, lightgbm, catboost, adaboost, research-papers, curated-list, ensemble-learning

## Member repositories
- benedekrozemberczki/awesome-gradient-boosting-papers (main) score 58

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:22.743746+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 2026-08-30T07:00:28.000015+00:00, confidence not recorded.
  - readme: https://github.com/benedekrozemberczki/awesome-gradient-boosting-papers (fetched 2026-08-28T04:03:22.743746+00:00, sha 185d26626d53)
- Data as of 2026-08-30T08:39:29.467469+00:00.