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On the interpretation of linear Riemannian tangent space model
  parameters in M/EEG

On the interpretation of linear Riemannian tangent space model parameters in M/EEG

30 July 2021
Reinmar J. Kobler
J. Hirayama
Lea Hehenberger
G. Müller-Putz
M. Kawanabe
ArXivPDFHTML

Papers citing "On the interpretation of linear Riemannian tangent space model parameters in M/EEG"

6 / 6 papers shown
Title
SPD Learning for Covariance-Based Neuroimaging Analysis: Perspectives, Methods, and Challenges
SPD Learning for Covariance-Based Neuroimaging Analysis: Perspectives, Methods, and Challenges
Ce Ju
Reinmar J. Kobler
Antoine Collas
M. Kawanabe
Cuntai Guan
Bertrand Thirion
41
0
0
26 Apr 2025
Explainable artificial intelligence approaches for brain-computer
  interfaces: a review and design space
Explainable artificial intelligence approaches for brain-computer interfaces: a review and design space
Param S. Rajpura
H. Cecotti
Y. Meena
24
6
0
20 Dec 2023
Graph Neural Networks on SPD Manifolds for Motor Imagery Classification:
  A Perspective from the Time-Frequency Analysis
Graph Neural Networks on SPD Manifolds for Motor Imagery Classification: A Perspective from the Time-Frequency Analysis
Ce Ju
Cuntai Guan
32
21
0
25 Oct 2022
SPD domain-specific batch normalization to crack interpretable
  unsupervised domain adaptation in EEG
SPD domain-specific batch normalization to crack interpretable unsupervised domain adaptation in EEG
Reinmar J. Kobler
J. Hirayama
Qibin Zhao
M. Kawanabe
16
53
0
02 Jun 2022
Tensor-CSPNet: A Novel Geometric Deep Learning Framework for Motor
  Imagery Classification
Tensor-CSPNet: A Novel Geometric Deep Learning Framework for Motor Imagery Classification
Ce Ju
Cuntai Guan
13
55
0
05 Feb 2022
Deep Optimal Transport for Domain Adaptation on SPD Manifolds
Deep Optimal Transport for Domain Adaptation on SPD Manifolds
Ce Ju
Cuntai Guan
48
3
0
15 Jan 2022
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