activity
20242026
most citedLEL: Lipschitz Continuity Constrained Ensemble Learning for Efficient EEG-Based Intra-subject Emotion Recognition

3 citations · 4 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2026

SUP-MCRL: Subject-aware Unified Pseudo-feature Coded Multimodal Contrastive Representation Learning for EEG Visual Decoding

Shengyu Gong, Weiming Zeng, Yueyang Li +4

Non-invasive brain-computer interfaces exhibit significant performance degradation when moving from controlled laboratory stimuli to real-world natural images. This degradation occ…

eess.SP2026

TGSD: Topology-Guided State-Space Diffusion Framework for EEG Spatial Super-Resolution

Zijian Kang, Weiming Zeng, Yueyang Li +4

Low-density EEG is more suitable for wearable and IoT-based brain sensing, but sparse electrode sampling often lacks sufficient spatial information to characterize cross-regional n…

cs.CV2025★ 3 cited

LEL: Lipschitz Continuity Constrained Ensemble Learning for Efficient EEG-Based Intra-subject Emotion Recognition

Shengyu Gong, Yueyang Li, Zijian Kang +6

Accurate and efficient recognition of emotional states is critical for human social functioning, and impairments in this ability are associated with significant psychosocial diffic…

cs.HC2025

Hypergraph Multi-Modal Learning for EEG-based Emotion Recognition in Conversation

Zijian Kang, Yueyang Li, Shengyu Gong +6

Emotional Recognition in Conversation (ERC) is valuable for diagnosing health conditions such as autism and depression, and for understanding the emotions of individuals who strugg…

cs.CV2025★ 1 cited

Information Bottleneck-Guided Heterogeneous Graph Learning for Interpretable Neurodevelopmental Disorder Diagnosis

Yueyang Li, Lei Chen, Wenhao Dong +9

Developing interpretable models for neurodevelopmental disorders (NDDs) diagnosis presents significant challenges in effectively encoding, decoding, and integrating multimodal neur…

cs.CV2024

Neural-MCRL: Neural Multimodal Contrastive Representation Learning for EEG-based Visual Decoding

Yueyang Li, Zijian Kang, Shengyu Gong +5

Decoding neural visual representations from electroencephalogram (EEG)-based brain activity is crucial for advancing brain-machine interfaces (BMI) and has transformative potential…

cs.CV2024

A Tale of Single-channel Electroencephalogram: Devices, Datasets, Signal Processing, Applications, and Future Directions

Yueyang Li, Weiming Zeng, Wenhao Dong +8

Single-channel electroencephalogram (EEG) is a cost-effective, comfortable, and non-invasive method for monitoring brain activity, widely adopted by researchers, consumers, and cli…