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Yangxuan Zhou

4 accepted papers

2025

BrainUICL: An Unsupervised Individual Continual Learning Framework for EEG Applications

ICLR 2025poster

Electroencephalography (EEG) is a non-invasive brain-computer interface technology used for recording brain electrical activity. It plays an important role in human life and has been widely uesd in real life, including sleep staging, emotion recognition, and motor imagery. However, existing EEG-rela…

Cited by 1SourcePDFScholar
2025

CBraMod: A Criss-Cross Brain Foundation Model for EEG Decoding

ICLR 2025poster

Electroencephalography (EEG) is a non-invasive technique to measure and record brain electrical activity, widely used in various BCI and healthcare applications. Early EEG decoding methods rely on supervised learning, limited by specific tasks and datasets, hindering model performance and generaliza…

2025

Personalized Sleep Staging Leveraging Source-free Unsupervised Domain Adaptation

AAAI 2025technical

Sleep staging is important for monitoring sleep quality and diagnosing sleep-related disorders. Recently, numerous deep learning-based models have been proposed for automatic sleep staging using polysomnography recordings. Most of them are trained and tested on the same labeled datasets which result…

2025

SPICED: A Synaptic Homeostasis-Inspired Framework for Unsupervised Continual EEG Decoding

NeurIPS 2025poster

Human brain achieves dynamic stability-plasticity balance through synaptic homeostasis, a self-regulatory mechanism that stabilizes critical memory traces while preserving optimal learning capacities. Inspired by this biological principle, we propose SPICED: a neuromorphic framework that integrates…

Cited by 0SourceScholar