Learning active subspaces and discovering important features with Gaussian radial basis functions neural networks
- DOI
- 10.1016/j.neunet.2024.106335
- Published
- 2024-08
- Container
- Neural Networks
- Publisher
- Elsevier BV
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- supportingDOI registered: A matching record was returned by Crossref.
- supportingDOI resolves: A matching record was returned by Crossref.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.1016/j.neunet.2024.106335,
title = {Learning active subspaces and discovering important features with Gaussian radial basis functions neural networks},
author = {Danny D’Agostino and Ilija Ilievski and Christine Annette Shoemaker},
year = {2024},
journal = {Neural Networks},
doi = {10.1016/j.neunet.2024.106335},
url = {https://doi.org/10.1016/j.neunet.2024.106335}
}RIS
TY - JOUR TI - Learning active subspaces and discovering important features with Gaussian radial basis functions neural networks AU - Danny D’Agostino AU - Ilija Ilievski AU - Christine Annette Shoemaker PY - 2024 JO - Neural Networks DO - 10.1016/j.neunet.2024.106335 UR - https://doi.org/10.1016/j.neunet.2024.106335 ER -
APA
D’Agostino, D., Ilievski, I., & Shoemaker, C. A. (2024). Learning active subspaces and discovering important features with Gaussian radial basis functions neural networks. Neural Networks. https://doi.org/10.1016/j.neunet.2024.106335
Source records
- crossref · retrieved 2026-11-10T13:58:51.955Z