Machine learning for decoding spin-zero and octupole excitations

Authors

Institutions

Publication Details

Journal
Physical review. C
Published
2025-05-28
DOI
https://doi.org/10.1103/vjwy-m9xv
Citations
4
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
9.92
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Machine learning for decoding spin-zero and octupole excitations

Karl J. Friston
4 citations
Physical review. C
Neural Networks and Applications
9.92
article

Machine learning for decoding spin-zero and octupole excitations

Karl J. Friston
article en
4 citations

Abstract

No abstract available for this paper.
Physical review. CVol. 111(6)
Université Paris-Saclay (FR), Huzhou Normal University (CN), China Institute of Atomic Energy (CN), Institute of Modern Physics (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 2%
Neural Networks and Applications
9.92
DOISourceOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Machine learning for decoding spin-zero and octupole excitations — Karl J. Friston · Physical review. C (2025) | TGRS Research Map | TGRS