SCIESCOPUSQ1
Machine Learning-Science and Technology
IOP Publishing Ltd, United States
Machine Learning-Science and Technology is an academic journal published by IOP Publishing Ltd (United States). Identifiers: eISSN 2632-2153. Indexed in SCIE, SCOPUS. Metrics: JIF 4.6, CiteScore 7.7, SJR 1.119, SNIP 1.39. Subject areas: ARTIFICIAL INTELLIGENCE, COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS, MULTIDISCIPLINARY SCIENCES. tlooto lists 1,798 papers from this journal.
CiteScore
7.70
Métrica de citas de Scopus
SJR
1.119
Ranking SCImago
SNIP
1.39
Impacto normalizado por fuente
Rango percentil
-
Percentil del JIF
Perfil de la revista
- ISSN
- -
- eISSN
- 2632-2153
- Abreviatura
- MACH LEARN-SCI TECHN
- Editorial
- IOP Publishing Ltd
- País
- United States
categorías de Web of Science
SCIEARTIFICIAL INTELLIGENCE, COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS, MULTIDISCIPLINARY SCIENCES
categorías ASJC de Scopus
170217091712
Palabras clave
Computer Science, Artificial Intelligence | Computer Science, Interdisciplinary Applications | Multidisciplinary Sciences
Papers in this journal
Recent papers
- Crystal generation using the fully differentiable pipeline and latent space optimization
2026
- Quantum complete graph self-attention network for particle flow classification
2026
- Error estimates for a physics-informed neural network in solving KdV equations
2026
- Convolutional neural network-driven preconditioners for conjugate gradients
2026
- UPD-Diff: a unified precipitation downscaling method based on multi-stream elucidating diffusion model
2026
Most cited papers
- Self-referencing embedded strings (SELFIES): A 100% robust molecular string representation
2019 · 929 citations
- The MLIP package: moment tensor potentials with MPI and active learning
2020 · 627 citations
- Chemformer: a pre-trained transformer for computational chemistry
2021 · 453 citations
- Data-driven discovery of Koopman eigenfunctions for control
2017 · 400 citations
- Graph neural networks in particle physics
2020 · 346 citations