Machine Learning: Science and Technology

eISSN: 2632-2153pISSN: 2632-2153
JournalOpen Access

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Key Metrics

CiteScore
4
Impact Factor
5 - 10
SNIP
1
4
Time to Publish
time-to-publish View Chart
5  Mo

Journal Specifications

Indexed in the following public directories

  • Web of Science
  • Scopus
  • DOAJ
  • Inspec
  • SJR
Overview
  • Publisher
    Institute of Physics Publishing
  • Language
    English
  • Frequency
    Quarterly
  • Article Processing Charges
    GBP 1600
  • Publication Time
    5
  • Editorial Review Process
    Blind peer review
General Details
Publication Details
Editorial Review Detail
Information for authors
View less
Time to Publish
Time to publish distribution
Articles published in year 2022
Time to publish index
Months% Papers published
0-3 5%
4-6 64%
7-9 24%
>9 8%

Topics Covered

Machine learning
Optical tweezers
Scientific literature
Materials science
Active learning
Tungsten disulfide
Dusty plasma
Coherent control
Uncertainty quantification
Artificial neural network
Chemical space
Optical measurements
Deep learning
Particle physics
Feature selection
Complete intersection
Reinforcement learning
Ferroelectric hysteresis
Quantum field theory
Survey propagation

Recently Published Papers

FAQs

How frequently is the Machine Learning: Science and Technology published? Faqs

Machine Learning: Science and Technology is published Quarterly.

Who is the publisher of Machine Learning: Science and Technology? Faqs

The publisher of Machine Learning: Science and Technology is Institute of Physics Publishing.

How can I view the journal metrics of Machine Learning: Science and Technology on editage? Faqs

For the Machine Learning: Science and Technology metrics, please refer to the section above on the page.

What is the eISSN and pISSN number of Machine Learning: Science and Technology? Faqs

The eISSN number is 2632-2153 and pISSN number is 2632-2153 for Machine Learning: Science and Technology.

What is the focus of this journal? Faqs

The journal covers a wide range of topics inlcuding Machine learning, Optical tweezers, Scientific literature, Materials science, Active learning, Tungsten disulfide, Dusty plasma, Coherent control, Uncertainty quantification, Artificial neural network, Chemical space, Optical measurements, Deep learning, Particle physics, Feature selection, Complete intersection, Reinforcement learning, Ferroelectric hysteresis, Quantum field theory, Survey propagation.

Why is it important to find the right journal for my research? Faqs

Choosing the right journal ensures that your research reaches the most relevant audience, thereby maximizing its scholarly impact and contribution to the field.

Can the choice of journal affect my academic career? Faqs

Absolutely. Publishing in reputable journals can enhance your academic profile, making you more competitive for grants, tenure, and other professional opportunities.

Is it advisable to target high-impact journals only? Faqs

While high-impact journals offer greater visibility, they are often highly competitive. It's essential to balance the journal's impact factor with the likelihood of your work being accepted.