Machine Learning-Science and Technology

简称：MACH LEARN-SCI TECHN

ISSN：2632-2153

ESSN：2632-2153

所属分区：1区

出版地：ENGLAND

出版周期：Quarterly

创刊时间：2020

研究方向：Multiple-

Machine Learning-Science and Technology英文简介

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

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