---
title: "jax-ml/jax: papers citing this GitHub repository"
description: "28 papers in the tracked journals link to the GitHub repository jax-ml/jax in their Crossref records, the first in 2022; most of them (11) in 2025."
url: https://scholar4ai.com/code/github-jax-ml-jax
markdown_url: https://scholar4ai.com/code/github-jax-ml-jax.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "28 papers in the tracked journals link to the GitHub repository jax-ml/jax in their Crossref records, the first in 2022; most of them (11) in 2025. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# jax-ml/jax: papers linking to it

Research papers in the 480 tracked journals that link to jax-ml/jax (https://github.com/jax-ml/jax), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

- GitHub
- 36,568 stars
- 4,016 forks
- Python
- license Apache-2.0
- created 2018
- https://github.com/jax-ml/jax

All repositories: https://scholar4ai.com/code.md

## Key findings

- 28 papers in the tracked journals link to the GitHub repository jax-ml/jax in their Crossref records, the first in 2022; most of them (11) in 2025.
- By category: Operations Research (14), AI (11) and Statistics (2); the journals with the most are Mathematical Programming (4), Nature Machine Intelligence (4) and Computational Optimization and Applications (3).
- 2 of the papers build on one another: a later paper cites an earlier one that also links jax-ml/jax.

## By year

*Papers linking to jax-ml/jax by publication year*

| Year | Papers |
|---|---:|
| 2022 | 1 |
| 2023 | 2 |
| 2024 | 5 |
| 2025 | 11 |
| 2026 | 9 |

## Journals

*Journals whose papers link to jax-ml/jax most*

| Journal | Papers |
|---|---:|
| [Mathematical Programming](https://scholar4ai.com/journals/mathematical-programming.md) | 4 |
| [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 4 |
| [Computational Optimization and Applications](https://scholar4ai.com/journals/computational-optimization-and-applications.md) | 3 |
| [Optimization and Engineering](https://scholar4ai.com/journals/optimization-and-engineering.md) | 2 |
| [Mathematical Programming Computation](https://scholar4ai.com/journals/mathematical-programming-computation.md) | 2 |

## Family tree

Each paper sits under the earlier paper it builds on.

- [Majorization-minimization-based Levenberg–Marquardt method for constrained nonlinear least squares](https://doi.org/10.1007/s10589-022-00447-y) (Computational Optimization and Applications, 2023)
  - [Accelerated-gradient-based generalized Levenberg–Marquardt method with oracle complexity bound and local quadratic convergence](https://doi.org/10.1007/s10107-024-02154-4) (Mathematical Programming, 2024) — cites the paper above

## Papers

*Papers linking to jax-ml/jax, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2024-02-13 | [A computational framework for neural network-based variational Monte Carlo with Forward Laplacian](https://doi.org/10.1038/s42256-024-00794-x) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Ruichen Li, Haotian Ye, Du Jiang et al. | 40 | cites it |
| 2022-05-19 | [Deep autoencoders for acoustic anomaly detection: experiments with working machine and in-vehicle audio](https://doi.org/10.1007/s00521-022-07375-2) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Gabriel Coelho, Luís Miguel Matos, Pedro José Pereira et al. | 26 | cites it |
| 2025-06-06 | [A multimodal conversational agent for DNA, RNA and protein tasks](https://doi.org/10.1038/s42256-025-01047-1) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Bernardo P. de Almeida, Guillaume Richard, Hugo Dalla-Torre et al. | 26 | cites it |
| 2023-01-17 | [Majorization-minimization-based Levenberg–Marquardt method for constrained nonlinear least squares](https://doi.org/10.1007/s10589-022-00447-y) | [Computational Optimization and Applications](https://scholar4ai.com/journals/computational-optimization-and-applications.md) | Naoki Marumo, Takayuki Okuno, Akiko Takeda | 22 | cites it |
| 2025-08-19 | [Topic-aware influence maximization with deep reinforcement learning and graph attention networks](https://doi.org/10.1007/s10618-025-01133-3) | [Data Mining and Knowledge Discovery](https://scholar4ai.com/journals/data-mining-and-knowledge-discovery.md) | Taha Halal, Bogdan Cautis, Benoît Groz et al. | 7 | cites it |
| 2025-03-24 | [Going faster to see further: graphics processing unit-accelerated value iteration and simulation for perishable inventory control using JAX](https://doi.org/10.1007/s10479-025-06551-6) | [Annals of Operations Research](https://scholar4ai.com/journals/annals-of-operations-research.md) | Joseph Farrington, Wai Keong Wong, Kezhi Li et al. | 5 | cites it |
| 2026-03-04 | [Generalized policy improvement for efficient and robust multi-objective reinforcement learning](https://doi.org/10.1007/s10458-026-09736-w) | [Autonomous Agents and Multi-Agent Systems](https://scholar4ai.com/journals/autonomous-agents-and-multi-agent-systems.md) | Lucas N. Alegre, Ana L. C. Bazzan, Diederik M. Roijers et al. | 4 | cites it |
| 2023-07-12 | [Complexity analysis of interior-point methods for second-order stationary points of nonlinear semidefinite optimization problems](https://doi.org/10.1007/s10589-023-00501-3) | [Computational Optimization and Applications](https://scholar4ai.com/journals/computational-optimization-and-applications.md) | Shun Arahata, Takayuki Okuno, Akiko Takeda | 3 | cites it |
| 2024-06-04 | [Universal heavy-ball method for nonconvex optimization under Hölder continuous Hessians](https://doi.org/10.1007/s10107-024-02100-4) | [Mathematical Programming](https://scholar4ai.com/journals/mathematical-programming.md) | Naoki Marumo, Akiko Takeda | 3 | cites it |
| 2025-11-19 | [Empirical evaluation of normalizing flows in Markov chain Monte Carlo](https://doi.org/10.1007/s10994-025-06900-3) | [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | David Nabergoj, Erik Štrumbelj | 3 | cites it |
| 2026-03-25 | [Machine learning global atomic representations with Euclidean fast attention](https://doi.org/10.1038/s42256-026-01195-y) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | J. Thorben Frank, Stefan Chmiela, Klaus-Robert Müller et al. | 3 | cites it |
| 2026-08-17 | [A simultaneous approach for training neural differential-algebraic systems of equations](https://doi.org/10.1007/s10589-026-00823-y) | [Computational Optimization and Applications](https://scholar4ai.com/journals/computational-optimization-and-applications.md) | Laurens R. Lueg, Victor Manuel Cunha Alves, Daniel Schicksnus et al. | 3 | cites it |
| 2024-07-04 | [Efficient Shapley performance attribution for least-squares regression](https://doi.org/10.1007/s11222-024-10459-9) | [Statistics and Computing](https://scholar4ai.com/journals/statistics-and-computing.md) | Logan Bell, Nikhil Devanathan, Stephen Boyd | 2 | cites it |
| 2024-10-29 | [SMT efficiency in supervised ML methods: a throughput and interference analysis](https://doi.org/10.1186/s40537-024-01013-5) | [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | Lucía Pons, Marta Navarro, Salvador Petit et al. | 2 | cites it |
| 2024-11-04 | [Accelerated-gradient-based generalized Levenberg–Marquardt method with oracle complexity bound and local quadratic convergence](https://doi.org/10.1007/s10107-024-02154-4) | [Mathematical Programming](https://scholar4ai.com/journals/mathematical-programming.md) | Naoki Marumo, Takayuki Okuno, Akiko Takeda | 2 | cites it |
| 2025-12-31 | [Reusability report: Optimizing T count in general quantum circuits with AlphaTensor-Quantum](https://doi.org/10.1038/s42256-025-01166-9) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Remmy A. M. Zen, Maximilian Nägele, Florian Marquardt | 2 | cites it |
| 2026-03-03 | [Risk-sensitive actor-critic with static spectral risk measures for online and offline reinforcement learning](https://doi.org/10.1016/j.eswa.2026.131838) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Mehrdad Moghimi, Hyejin Ku | 2 | cites it |
| 2026-08-10 | [Condensed interior-point methods for scalable nonlinear programming on GPUs](https://doi.org/10.1007/s12532-026-00335-0) | [Mathematical Programming Computation](https://scholar4ai.com/journals/mathematical-programming-computation.md) | François Pacaud, Sungho Shin, Alexis Montoison et al. | 2 | cites it |
| 2025-02-13 | [CDOpt: a Python package for a class of Riemannian optimization](https://doi.org/10.1007/s12532-025-00277-z) | [Mathematical Programming Computation](https://scholar4ai.com/journals/mathematical-programming-computation.md) | Nachuan Xiao, Xiaoyin Hu, Xin Liu et al. | 1 | cites it |
| 2025-05-28 | [Graph spring neural ODEs for link sign prediction](https://doi.org/10.1007/s10994-025-06794-1) | [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | Andrin Rehmann, Alexandre Bovet | 1 | cites it |
| 2025-12-15 | [Code generation for solving and differentiating through convex optimization problems](https://doi.org/10.1007/s11081-025-10057-2) | [Optimization and Engineering](https://scholar4ai.com/journals/optimization-and-engineering.md) | Maximilian Schaller, Stephen Boyd | 1 | cites it |
| 2026-03-03 | [Efficient inference in first passage time models](https://doi.org/10.1007/s11222-026-10854-4) | [Statistics and Computing](https://scholar4ai.com/journals/statistics-and-computing.md) | Sicheng Liu, Alexander Fengler, Michael J. Frank et al. | 1 | cites it |
| 2025-04-24 | [Ozone: an open-source ordinary differential equation solver for gradient-based optimization](https://doi.org/10.1007/s11081-025-09967-y) | [Optimization and Engineering](https://scholar4ai.com/journals/optimization-and-engineering.md) | Mark Z. Sperry, John Tan Teng Hwang | 0 | cites it |
| 2025-08-13 | [Error Bound Analysis of Physics-Informed Neural Networks for Solving Nonlinear Projection Equations](https://doi.org/10.1007/s10957-025-02793-3) | [Journal of Optimization Theory and Applications](https://scholar4ai.com/journals/journal-of-optimization-theory-and-applications.md) | Dawen Wu, Abdel Lisser | 0 | cites it |
| 2025-10-01 | [Transformation of Bi-level Transit Network Design Problem into Single-objective Unconstrained Optimization](https://doi.org/10.1007/s11067-025-09698-8) | [Networks and Spatial Economics](https://scholar4ai.com/journals/networks-and-spatial-economics.md) | Jincheol Lee, Gyeongjun Kim, Keemin Sohn | 0 | cites it |
| 2026-04-07 | [Fast finite-sum optimization via cyclically-sampled Hessian averaging methods](https://doi.org/10.1007/s10107-026-02354-0) | [Mathematical Programming](https://scholar4ai.com/journals/mathematical-programming.md) | Thomas O’Leary-Roseberry, Raghu Bollapragada | 0 | cites it |
| 2026-07-08 | [Strongly convex maximization via the Frank-Wolfe algorithm with the Kurdyka-Łojasiewicz inequality](https://doi.org/10.1007/s10107-026-02381-x) | [Mathematical Programming](https://scholar4ai.com/journals/mathematical-programming.md) | Fatih S. Aktaş, Christian Kroer | 0 | cites it |
| 2026-09-25 | [Are farmers algorithm-averse? The case of decision support tools in crop management](https://doi.org/10.1016/j.foodpol.2026.103193) | [Food Policy](https://scholar4ai.com/journals/food-policy.md) | Anna Massfeller, Daniel Hermann, Alexa Leyens et al. | 0 | cites it |

## How this is measured

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

## Cite this page

Scholar4AI. (2026). jax-ml/jax: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-jax-ml-jax

```bibtex
@misc{scholar4ai-code-github-jax-ml-jax,
  author = {{Scholar4AI}},
  title = {jax-ml/jax: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-jax-ml-jax}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).