SynNeura: Event-driven liquid-spiking dynamics for weakly supervised multimodal temporal alignment.

Zhang Y, Liu Y

DOI: 10.1016/j.neunet.2026.109583
Published: 2026 Sep 2
Container: Neural networks : the official journal of the International Neural Network Society
Publisher: Not recorded
Open access: no

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Cite this work

BibTeX

@article{allodium:10.1016/j.neunet.2026.109583,
  title = {SynNeura: Event-driven liquid-spiking dynamics for weakly supervised multimodal temporal alignment.},
  author = {Zhang Y and Liu Y},
  year = {2026},
  journal = {Neural networks : the official journal of the International Neural Network Society},
  doi = {10.1016/j.neunet.2026.109583},
  url = {https://doi.org/10.1016/j.neunet.2026.109583}
}

RIS

TY  - JOUR
TI  - SynNeura: Event-driven liquid-spiking dynamics for weakly supervised multimodal temporal alignment.
AU  - Zhang Y
AU  - Liu Y
PY  - 2026
JO  - Neural networks : the official journal of the International Neural Network Society
DO  - 10.1016/j.neunet.2026.109583
UR  - https://doi.org/10.1016/j.neunet.2026.109583
ER  -

APA

Y, Z., & Y, L. (2026). SynNeura: Event-driven liquid-spiking dynamics for weakly supervised multimodal temporal alignment.. Neural networks : the official journal of the International Neural Network Society. https://doi.org/10.1016/j.neunet.2026.109583

Source records

pubmed · retrieved 2026-09-25T23:04:34.325Z
europe-pmc · retrieved 2026-09-25T23:04:34.343Z