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SplitSEE: A Splittable Self-supervised Framework for Single-Channel EEG Representation Learning

SplitSEE: A Splittable Self-supervised Framework for Single-Channel EEG Representation Learning

Industrial Conference on Data Mining (IDM), 2024
Rikuto Kotoge
Zheng Chen
Tasuku Kimura
Yasuko Matsubara
Takufumi Yanagisawa
H. Kishima
Yasushi Sakurai
ArXiv (abs)PDFHTML

Papers citing "SplitSEE: A Splittable Self-supervised Framework for Single-Channel EEG Representation Learning"

2 / 2 papers shown
Title
EvoBrain: Dynamic Multi-Channel EEG Graph Modeling for Time-Evolving Brain Networks
EvoBrain: Dynamic Multi-Channel EEG Graph Modeling for Time-Evolving Brain Networks
Rikuto Kotoge
Zheng Chen
Tasuku Kimura
Yasuko Matsubara
Takufumi Yanagisawa
H. Kishima
Yasushi Sakurai
36
0
0
19 Sep 2025
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
Mathilde Caron
Ishan Misra
Julien Mairal
Priya Goyal
Piotr Bojanowski
Armand Joulin
OCLSSL
865
4,543
0
17 Jun 2020