ISSN 1805-3610  (Print)
ISSN 1805-3629  (On-line)

DOI prefix: 10.13164/ma

Editorial Board

Instructions to Authors


Publication Ethics and Publication Malpractice Statement


Mathematics for applications publishes original papers of a high scientific level in all branches of mathematics with an emphasis on applications of results in mathematics itself and other disciplines. Published by the Institute of Mathematics of Brno University of Technology since 2012, this international journal builds on Publications of Technical and Scientific Papers of the Technical University of Brno (ISBN: 80-214-020-X), a renowned journal published by the University until 1990's. It had provided a platform for the international mathematical community to publish research papers and, after its disappearance, we decided to found a new mathematical journal to continue this service. 
Issued biannually on an open-access basis, the journal has English as the only language of communication. The manuscripts of papers for publication should by prepared electronically using the journal style – see Instructions for Authors – and sent to .

 Mathematics for Applications
 Institute of Mathematics
 Faculty of Mechanical Engineering
 Brno University of Technology
 Technická 2896/2
 616 69 Brno
 Czech Republic

  Recent Volumes :  
   Vol 8. (2019):  No. 1    No. 2
   Vol 7. (2018):  No. 1    No. 2
   Vol 6. (2017):  No. 1    No. 2
   Vol 5. (2016):
  No. 1    No. 2
   Vol 4. (2015):  No. 1    No. 2
   Vol 3. (2014):
  No. 1    No. 2
   Vol 2. (2013):  No. 1    No. 2
   Vol 1. (2012):  No. 1    No. 2

Latest Issue

Vol. 8. No. 2. (2019)

E. Fokoué
On the versatility and polyvalence of certain statistical learning machines

L. Khinkis
On a global measure of nonlinearity and its application in parameter estimation in nonlinear regression
DOI: 10.13164/ma.2019.07

S. Raja and E. Fokoué
Multi-stage fault warning for large electric grids using anomaly detection and machine learning
DOI: 10.13164/ma.2019.08

J. T. Whelan and A. Wodon
Prediction and evaluation in College Hockey using the Bradley–Terry–Zermelo model
DOI: 10.13164/ma.2019.9

P. Sah and E. Fokoué
What do Asian and non-Asian scriptures have in common? An applied statistical machine learning inquiry
DOI: 10.13164/ma.2019.10

E. A. Ogundepo and E. Fokoué
An empirical demonstration of the no free lunch theorem
DOI: 10.13164/ma.2019.11

E. Fokoué
On the ubiquity of the Bayesian paradigm in statistical machine learning and data science
DOI: 10.13164/ma.2019.12