英文簡介Machine Learning-science And Technology期刊介紹

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

期刊簡介Machine Learning-science And Technology期刊介紹

《Machine Learning-science And Technology》自2020出版以來，是一本物理與天體物理優(yōu)秀雜志。致力于發(fā)表原創(chuàng)科學(xué)研究結(jié)果，并為物理與天體物理各個(gè)領(lǐng)域的原創(chuàng)研究提供一個(gè)展示平臺(tái)，以促進(jìn)物理與天體物理領(lǐng)域的的進(jìn)步。該刊鼓勵(lì)先進(jìn)的、清晰的闡述，從廣泛的視角提供當(dāng)前感興趣的研究主題的新見解，或?qū)彶槎嗄陙砟硞€(gè)重要領(lǐng)域的所有重要發(fā)展。該期刊特色在于及時(shí)報(bào)道物理與天體物理領(lǐng)域的最新進(jìn)展和新發(fā)現(xiàn)新突破等。該刊近一年未被列入預(yù)警期刊名單，目前已被權(quán)威數(shù)據(jù)庫SCIE收錄，得到了廣泛的認(rèn)可。

該期刊投稿重要關(guān)注點(diǎn)：

• 預(yù)計(jì)審稿時(shí)間：約Submission to first decision before peer review: 3 days; Submission to first decision after peer review: 49 days; 13 Weeks
• 國際TOP期刊
• 物理與天體物理
• COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
• SCIE
• 中科院2區(qū)
• 非預(yù)警