Chenglong Yu — accepted AI-conference papers

2026

D$^2$-FOSA: Dual-Diffusion Guided EEG-to-Image Reconstruction with Frequency-Oriented Semantic Alignment

Chenglong Yu, Shuai Shen, Xiangsheng Li, Yang Li

CVPR 2026

Reconstructing visual semantics from Electroencephalography (EEG) signals enables a deeper understanding of human visual cognition and supports next-generation brain-computer interface (BCI) applications.Despite notable advances in recent years, most existing EEG encoders still struggle to capture t

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2026

HyperDiag: Temporal–Regional Hypergraph Learning via Topology-Enhanced State Propagation for Brain Disease Diagnosis

Yulan Ma, Fangkun Li, Wenchao Yang, Qian Si, Chenglong Yu, Yang Li

AAAI 2026technical

Dynamic brain networks provide a powerful representation for capturing temporal variations in functional brain connectivity and have gained increasing attention in brain disease diagnosis. However, most existing methods extract features from isolated time windows, making it difficult to capture the

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