26 citations · 27 across the 3 of their papers we have counts for
3 papers
GEFM: Graph-Enhanced EEG Foundation Model
Limin Wang, Toyotaro Suzumura, Hiroki Kanezashi
Electroencephalography (EEG) signals provide critical insights for applications in disease diagnosis and healthcare. However, the scarcity of labeled EEG data poses a significant c…
Graph Adapter of EEG Foundation Models for Parameter Efficient Fine Tuning
Toyotaro Suzumura, Hiroki Kanezashi, Shotaro Akahori
In diagnosing neurological disorders from electroencephalography (EEG) data, foundation models such as Transformers have been employed to capture temporal dynamics. Additionally, G…
Revisiting Mobility Modeling with Graph: A Graph Transformer Model for Next Point-of-Interest Recommendation
Xiaohang Xu, Toyotaro Suzumura, Jiawei Yong +5
Next Point-of-Interest (POI) recommendation plays a crucial role in urban mobility applications. Recently, POI recommendation models based on Graph Neural Networks (GNN) have been…