5 papers
EEG-SeeGraph: Interpreting functional connectivity disruptions in dementias via sparse-explanatory dynamic EEG-graph learning
Fengcheng Wu, Zhenxi Song, Guoyang Xu +4
Robust and interpretable dementia diagnosis from noisy, non-stationary electroencephalography (EEG) is clinically essential yet remains challenging. To this end, we propose SeeGrap…
Invariant Representation Guided Multimodal Sentiment Decoding with Sequential Variation Regularization
Guoyang Xu, Zhenxi Song, Junqi Xue +3
Achieving consistent sentiment representation across diverse modalities remains a key challenge in multimodal sentiment analysis. However, rapid emotional fluctuations over time of…
Senti-iFusion: An Integrity-centered Hierarchical Fusion Framework for Multimodal Sentiment Analysis under Uncertain Modality Missingness
Liling Li, Guoyang Xu, Xiongri Shen +4
Multimodal Sentiment Analysis (MSA) is critical for human-computer interaction but faces challenges when the modalities are incomplete or missing. Existing methods often assume pre…
SSVEP-BiMA: Bifocal Masking Attention Leveraging Native and Symmetric-Antisymmetric Components for Robust SSVEP Decoding
Yuxin Liu, Zhenxi Song, Guoyang Xu +5
Brain-computer interface (BCI) based on steady-state visual evoked potentials (SSVEP) is a popular paradigm for its simplicity and high information transfer rate (ITR). Accurate an…
EEG-ReMinD: Enhancing Neurodegenerative EEG Decoding through Self-Supervised State Reconstruction-Primed Riemannian Dynamics
Zirui Wang, Zhenxi Song, Yi Guo +4
The development of EEG decoding algorithms confronts challenges such as data sparsity, subject variability, and the need for precise annotations, all of which are vital for advanci…