Journal profile · Mathematics-Statistics and Probability
Mathematical Statistics and Learning
ISSN 2520-2316 · eISSN 2520-2324 · EMS Press · Germany
Mathematical Statistics and Learning: diamond open access (no APC); no APC; review about 80 weeks (community reports); 7 articles in 2025; indexed in Scopus.
Scope
Aims, scope and focus
Mathematical Statistics and Learning is published by EMS Press. By OpenAlex counts of its recent articles, its largest topics are Statistical Methods and Inference, Stochastic Gradient Optimization Techniques and Probability and Statistical Research, together about 36.2% of its articles. Its main subfields are Statistics and Probability and Artificial Intelligence. (generated from OpenAlex topic counts and CAS ranking data)
Mathematical Statistics and Learning is devoted to research articles of the highest quality in all aspects of mathematical statistics and learning, including those studied in traditional areas of statistics and in machine learning as well as in theoretical computer science and signal processing.
From the journal's Aims & Scope
Research area (LetPub): Mathematics-Statistics and Probability
Main research topics OpenAlex counts of recent articles; shares are approximate
- Statistical Methods and InferenceMathematics20.1%
- Stochastic Gradient Optimization TechniquesComputer Science8.1%
- Probability and Statistical ResearchMathematics8.1%
- Sparse and Compressive Sensing TechniquesEngineering6.7%
- Complex Network Analysis TechniquesPhysics and Astronomy5.4%
- Bayesian Methods and Mixture ModelsComputer Science4.7%
- Markov Chains and Monte Carlo MethodsMathematics4.7%
- Complexity and Algorithms in GraphsComputer Science4%
Rankings & indexing
CAS ranking and database indexing
CAS Journal Ranking
CAS Journal Ranking, upgraded edition (March 2025)Not covered
Not covered by this edition.
CAS Xinrui Journal Ranking (March 2026)Not covered
Not covered by this edition.
CAS Journal Ranking, previous upgraded edition (December 2023)Not covered
Not covered by this edition.
CiteScore quartiles (Scopus, June 2026 release)
| Subject | Quartile | Rank | Percentile |
|---|---|---|---|
| Statistics and Probability | Q2 | 132/303 | 56th |
| Computational Theory and Mathematics | Q2 | 99/203 | 51st |
| Signal Processing | Q2 | 100/203 | 50th |
| Theoretical Computer Science | Q3 | 73/135 | 46th |
Scopus ranks journals by CiteScore within each subject: the 75th percentile and above is Q1, then a quartile every 25 points. A different system from the CAS zones.LetPub
Database indexing
ScopusDOAJLetPub
International journal early-warning lists: not listed in any editionLetPub
Indexing the journal's website claims
MathSciNetzbMATHPublisher website
As the journal's website lists them, not checked against each database; for Web of Science editions the records above apply.
Editions, and major and minor categories, are shown separately and never merged into one zone; check which edition your institution uses before you submit or report.
Metrics
Impact metrics and publication volume
Impact
- CiteScore 2026-06
- 2.5LetPub ·
- SJR 2026-06
- 0.96LetPub ·
- SNIP 2026-06
- 0.99LetPub ·
- h-index
- 15OpenAlex ·
- i10-index
- 19OpenAlex ·
- 2-year mean citedness
- 1.12OpenAlex ·
- Share of gold OA articles
- 0%LetPub ·
Articles by year OpenAlex count · 59 in total · the current year is incomplete
| Year | Articles | Open access | Citations |
|---|---|---|---|
| 2026 | 6 | 6 | 45 |
| 2025 | 7 | 7 | 93 |
| 2024 | 4 | 4 | 95 |
| 2023 | 5 | 5 | 78 |
| 2022 | 12 | 12 | 106 |
| 2021 | 7 | 7 | 113 |
Sources count differently and were observed at different times, so each source's own value is kept; "publisher" marks figures from the journal's website.
Review & acceptance
Review time and acceptance
- Average review time (community reports)
- about 80 weeksLetPub ·
- Submission to publication (journal-reported)
- about 80 weeksDOAJ ·
- Peer review
- Single anonymous peer reviewDOAJ
Community reports come from authors' own submissions (confidence 0.5) and are not a promise from the journal; for publisher figures, the journal's own definitions apply.
Fees & open access
APC and open-access policy
Diamond open access (no APC)DOAJ
Every article is open access and authors pay no article processing charge.
| Source | APC | Fee waiver | License | Observed |
|---|---|---|---|---|
| DOAJ | No APC | No | CC BY | |
| LetPub | No APC | No | — |
The journal's website is authoritative for fees; sources were observed at different times and each keeps its own value, without averaging.
Submission
Article types and submission policies (journal website)
Policy excerpts from the journal's websiteAuthorship, Publication ethics, License & copyright, Open access, Peer review, Preprints, Self-archiving
- Authorship
Papers must be written in English. Model summary
Papers to be considered for publication must be written in English.
Source ↗Publisher website ·- Publication ethics
Adheres to EMS Code of Practice and publisher's Code of Conduct and Publishing Ethics. Model summary
The journal is owned by the European Mathematical Society and it adheres to its Code of Practice and the publisher's Code of Conduct and Publishing Ethics.
Source ↗Publisher website ·- License & copyright
Open access articles are published under the CC-BY 4.0 license. Model summary
Open access articles are published under the CC-BY 4.0 license.
Source ↗Publisher website ·- Open access Open Access
Subscribe to Open (S2O) model; articles may be published open access with no author fees or article processing charges. Model summary
Mathematical Statistics and Learning is a Subscribe to Open (S2O) journal, which means that articles may be published open access. There are no author fees or article processing charges associated with this model of open access. Open access articles are published under the CC-BY 4.0 license. The articles that are not published with proper open access, are granted the so-called green open access, m…
Source ↗Publisher website ·- Peer review Peer Review
Peer review process is two-step single-blind, conducted by external reviewers selected by the editorial board. Model summary
Mathematical Statistics and Learning operates a two-step single-blind peer review process, conducted by external reviewers selected by the editorial board.
Source ↗Publisher website ·- Preprints
Conference proceedings papers may be considered if consistent with copyright agreements and with significant merit compared to the conference version. Model summary
Papers that contain results previously published or accepted at conference proceedings will be considered if the submission is consistent with copyright agreements and has significant merit compared to the conference version.
Source ↗Publisher website ·- Self-archiving
Non-OA articles get green open access: authors' final version can be posted in repositories or on institutional web pages without embargo; papers become freely accessible after five years. Model summary
The articles that are not published with proper open access, are granted the so-called green open access, meaning that the authors’ final version, not edited by the publisher yet, can be posted in institutional or other repositories, as well as on the authors’ institutional web pages without any embargo. These papers become freely accessible – but remain copyright protected – after five years.
Source ↗Publisher website ·
Excerpts are quoted from the journal's website; "model summary" lines are written by Workers AI and checked against the text. The journal's website is authoritative.
Profile
Publication details and official links
- Publisher
- EMS Press
- Country or region
- Germany
- Language
- English
- ISSN
- 2520-2316
- Electronic ISSN
- 2520-2324
- Official links
- Journal homepage ↗OpenAlex
- Author guidelines ↗LetPub
- Aims & Scope ↗LetPub
- APC information ↗DOAJ
- Open access statement ↗DOAJ
- License & copyright ↗DOAJ
- Peer review process ↗LetPub
- Editorial board ↗LetPub
FAQ
Frequently asked questions about Mathematical Statistics and Learning
How long does peer review take at Mathematical Statistics and Learning?
Authors report an average review time of about 80 weeks. Article statistics cover accepted papers only, publisher figures follow the journal's own definitions, and community reports come from authors' own submissions; none is a promise from the journal.
Which databases index Mathematical Statistics and Learning?
According to LetPub and DOAJ records, Mathematical Statistics and Learning is indexed in Scopus and DOAJ. The journal's website also lists MathSciNet and zbMATH; that list has not been checked against each database.
Is Mathematical Statistics and Learning open access, and what is the APC?
Mathematical Statistics and Learning is a diamond open-access journal (no APC). It charges no article processing charge.
Sources and updates
The facts on this page come from LetPub, OpenAlex, DOAJ, Publisher website; every figure is tagged with its source and the date it was observed, and conflicting values are kept per source. LetPub source page: view ↗ (archived 2026-08-25). Last updated: .