4 papers
Brain4FMs: A Benchmark of Foundation Models for Electrical Brain Signal
Fanqi Shen, Enhong Yang, Jiahe Li +5
Brain Foundation Models (BFMs) are transforming neuroscience by enabling scalable and transferable learning from neural signals, advancing both clinical diagnostics and cutting-edg…
Assembling the Mind's Mosaic: Towards EEG Semantic Intent Decoding
Jiahe Li, Junru Chen, Fanqi Shen +6
Enabling natural communication through brain-computer interfaces (BCIs) remains one of the most profound challenges in neuroscience and neurotechnology. While existing frameworks o…
Deep Learning-Powered Electrical Brain Signals Analysis: Advancing Neurological Diagnostics
Jiahe Li, Xin Chen, Fanqi Shen +7
Neurological disorders pose major global health challenges, driving advances in brain signal analysis. Scalp electroencephalography (EEG) and intracranial EEG (iEEG) are widely use…
Con4m: Context-aware Consistency Learning Framework for Segmented Time Series Classification
Junru Chen, Tianyu Cao, Jing Xu +4
Time Series Classification (TSC) encompasses two settings: classifying entire sequences or classifying segmented subsequences. The raw time series for segmented TSC usually contain…