Gradient-informed neural networks: Embedding prior beliefs for learning in low-data scenarios.
- DOI
- 10.1016/j.neunet.2026.108681
- Published
- 2026 Jul
- Container
- Neural networks : the official journal of the International Neural Network Society
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.neunet.2026.108681,
title = {Gradient-informed neural networks: Embedding prior beliefs for learning in low-data scenarios.},
author = {Aglietti F and Della Santa F and Piano A and Aglietti V},
year = {2026},
journal = {Neural networks : the official journal of the International Neural Network Society},
doi = {10.1016/j.neunet.2026.108681},
url = {https://doi.org/10.1016/j.neunet.2026.108681}
}RIS
TY - JOUR TI - Gradient-informed neural networks: Embedding prior beliefs for learning in low-data scenarios. AU - Aglietti F AU - Della Santa F AU - Piano A AU - Aglietti V PY - 2026 JO - Neural networks : the official journal of the International Neural Network Society DO - 10.1016/j.neunet.2026.108681 UR - https://doi.org/10.1016/j.neunet.2026.108681 ER -
APA
F, A., F, D. S., A, P., & V, A. (2026). Gradient-informed neural networks: Embedding prior beliefs for learning in low-data scenarios.. Neural networks : the official journal of the International Neural Network Society. https://doi.org/10.1016/j.neunet.2026.108681
Source records
- pubmed · retrieved 2026-09-26T11:47:17.426Z