Free Online Access
ISSN Imprimir: 2689-3967
Finalidades e escopo
The Journal of Machine Learning for Modeling and Computing (JMLMC) focuses on the study of machine learning methods for modeling and scientific computing. The scope of the journal includes, but is not limited to, research of the following types: (1) the use of machine learning techniques to model real-world problems such as physical systems, social sciences, biology, etc.; (2) the development of novel numerical strategies, in conjunction of machine learning methods, to facilitate practical computation; and (3) the fundamental mathematical and numerical analysis for understanding machine learning methods.
Editor-in-Chief: Dongbin Xiu
Call for Papers
The Journal of Machine Learning for Modeling and Computing (JMLMC) is seeking submissions from leaders in the field. If you would like to contribute, please submit your articles in Begell House submission site at Begell House Submission System
Please feel free to contact Editor-in-Chief Dongbin Xiu at email@example.com if you have any questions or need any assistance. Begell House can also be contacted at firstname.lastname@example.org.
Author instructions for the Journal of Machine Learning for Modeling and Computing can be found at: Instruction.pdf.
As part of the community reciprocation that furthers research in any field, authors who submit articles to JMLMC acknowledge that they may be asked to review other articles for the journal.Enquiries can be directed to Editor-in-Chief Dongbin Xiu at email@example.com.
Call for Papers: Computational Modeling and Machine Learning Applications to Biological, Bio-inspired, and Epidemiological Systems
Detailed instructions for submission can be found at:https://www.j-mlmc.com/forauthors/.
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