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期刊名
Machine Learning-Science and Technology
ISSN / eISSN
2632-2153 / 2632-2153
目标和范围
Machine Learning: Science and Technology™ is a multidisciplinary open access journal that bridges the application of machine learning across the sciences with advances in machine learning methods and theory as motivated by physical insights. Specifically, articles must fall into one of the following categories:
i) advance the state of machine learning-driven applications in the sciences,
or
ii) make conceptual, methodological or theoretical advances in machine learning with applications to, inspiration from, or motivated by scientific problems.
Particular areas of scientific application include (but are not limited to):
• Physics and space science
• Design and discovery of novel materials and molecules
• Materials characterisation techniques
• Simulation of materials, chemical processes and biological systems
• Atomistic and coarse-grained simulation
• Quantum computing
• Biology, medicine and biomedical imaging
• Geoscience (including natural disaster prediction) and climatology
• Particle Physics
• Simulation methods and high-performance computing
Conceptual or methodological advances in machine learning methods include those in (but are not limited to):
• Explainability, causality and robustness
• New (physics inspired) learning algorithms
• Neural network architectures
• Kernel methods
• Bayesian and other probabilistic methods
• Supervised, unsupervised and generative methods
• Novel computing architectures
• Codes and datasets
• Benchmark studies
研究方向
计算机:人工智能
综合性期刊
计算机:跨学科应用
CiteScore
9.10
查看趋势图
CiteScore 学科排名
类别 | 分区 | 排名 |
---|---|---|
Computer Science - Software | Q1 | #70/407 |
Computer Science - Human-Computer Interaction | Q1 | #26/145 |
Computer Science - Artificial Intelligence | Q1 | #73/350 |
Web of Science 核心收藏夹
Science Citation Index Expanded (SCIE) | Social Sciences Citation Index (SSCI) |
---|---|
Indexed | - |
类别 (Journal Citation Reports 2024) | 分区 |
---|---|
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | Q1 |
COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | Q1 |
MULTIDISCIPLINARY SCIENCES | Q1 |
出版国家或地区
ENGLAND
出版商
IOP PUBLISHING LTD
出版周期
Quarterly
出版年份
2020
年文章数
194
Open Access
YES
通讯方式
IOP PUBLISHING LTD, TEMPLE CIRCUS, TEMPLE WAY, BRISTOL, ENGLAND, BS1 6BE
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