Supervised Graph Representation Learning For Modeling The Relationship Between Structural And Functional Brain Connectivity

This video program is a part of the Premium package:

Supervised Graph Representation Learning For Modeling The Relationship Between Structural And Functional Brain Connectivity


  • IEEE MemberUS $11.00
  • Society MemberUS $0.00
  • IEEE Student MemberUS $11.00
  • Non-IEEE MemberUS $15.00
Purchase

Supervised Graph Representation Learning For Modeling The Relationship Between Structural And Functional Brain Connectivity

1 view
  • Share
Create Account or Sign In to post comments
In this paper, we propose a supervised graph representation learning method to model the relationship between brain functional connectivity (FC) and structural connectivity (SC) through a graph encoder-decoder system. The graph convolutional network (GCN)
In this paper, we propose a supervised graph representation learning method to model the relationship between brain functional connectivity (FC) and structural connectivity (SC) through a graph encoder-decoder system. The graph convolutional network (GCN)