Going deeper with morphologically detailed neural networks by simulation-based gradient propagation.

He G, Du K, Huang T

DOI: 10.3389/fncom.2026.1904220
Published: 2026
Container: Frontiers in computational neuroscience
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/fncom.2026.1904220,
  title = {Going deeper with morphologically detailed neural networks by simulation-based gradient propagation.},
  author = {He G and Du K and Huang T},
  year = {2026},
  journal = {Frontiers in computational neuroscience},
  doi = {10.3389/fncom.2026.1904220},
  url = {https://doi.org/10.3389/fncom.2026.1904220}
}

RIS

TY  - JOUR
TI  - Going deeper with morphologically detailed neural networks by simulation-based gradient propagation.
AU  - He G
AU  - Du K
AU  - Huang T
PY  - 2026
JO  - Frontiers in computational neuroscience
DO  - 10.3389/fncom.2026.1904220
UR  - https://doi.org/10.3389/fncom.2026.1904220
ER  -

APA

G, H., K, D., & T, H. (2026). Going deeper with morphologically detailed neural networks by simulation-based gradient propagation.. Frontiers in computational neuroscience. https://doi.org/10.3389/fncom.2026.1904220

Source records

pubmed · retrieved 2026-11-10T10:27:14.530Z