A unified foundation model for heterogeneous EEG signal modeling via language-aligned semi-supervised learning
- DOI
- 10.1016/j.neunet.2026.109544
- Published
- 2027-01
- Container
- Neural Networks
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.neunet.2026.109544,
title = {A unified foundation model for heterogeneous EEG signal modeling via language-aligned semi-supervised learning},
author = {Ziman Ye and Muyun Jiang and Jiaqi Zhu and Hao Zheng and Mengchi Rong and Fang Deng},
year = {2027},
journal = {Neural Networks},
doi = {10.1016/j.neunet.2026.109544},
url = {https://doi.org/10.1016/j.neunet.2026.109544}
}RIS
TY - JOUR TI - A unified foundation model for heterogeneous EEG signal modeling via language-aligned semi-supervised learning AU - Ziman Ye AU - Muyun Jiang AU - Jiaqi Zhu AU - Hao Zheng AU - Mengchi Rong AU - Fang Deng PY - 2027 JO - Neural Networks DO - 10.1016/j.neunet.2026.109544 UR - https://doi.org/10.1016/j.neunet.2026.109544 ER -
APA
Ye, Z., Jiang, M., Zhu, J., Zheng, H., Rong, M., & Deng, F. (2027). A unified foundation model for heterogeneous EEG signal modeling via language-aligned semi-supervised learning. Neural Networks. https://doi.org/10.1016/j.neunet.2026.109544
Source records
- crossref · retrieved 2026-09-25T17:30:01.492Z