4 papers
FSDBN: Foreground-Aware EEG-Visual Alignment via Dynamic Brain Networks
Yiheng Liu, Chuhang Zheng, Peiliang Gong +3
EEG-based visual decoding provides a non-invasive pathway for interpreting visual semantics. However, existing methods often overlook the perceptual asymmetry between foreground an…
Multi-Level Bidirectional Biomimetic Learning for EEG-Based Visual Decoding
Jingtao Liu, Peiliang Gong, Chuhang Zheng +2
EEG-based visual neural decoding aims to align neural responses with visual stimuli for tasks such as image retrieval. However, limited paired data and a fundamental mismatch betwe…
TAAM:Inductive Graph-Class Incremental Learning with Task-Aware Adaptive Modulation
Jingtao Liu, Xinming Zhang
Graph Continual Learning (GCL) aims to solve the challenges of streaming graph data. However, current methods often depend on replay-based strategies, which raise concerns like mem…
Task-Aware Adaptive Modulation: A Replay-Free and Resource-Efficient Approach For Continual Graph Learning
Jingtao Liu, Xinming Zhang
Continual Graph Learning(CGL)focuses on acquiring new knowledge while retaining previously learned information, essential for real-world graph applications. Current methods grapple…