Advancements in Simple Multigraph Convolution Networks by Xinjie Shen
Explore the latest innovations in simple multigraph convolution networks presented by Xinjie Shen from South China University of Technology. The research evaluates existing methods, such as PGCN, MGCN, and MIMO-GCN, and introduces novel techniques for building credible graphs through subgraph-level and edge-level voting from multigraphs. Detailed experiments and code resources are also shared for further exploration and implementation.
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Presentation Transcript
This PPT Simple Multigraph Convolution Networks Xinjie Shen South China University of Technology
Simple Multigraph Convolution Networks Existing multigraph convolution methods still have difficult in effectively solving the conflict between effectiveness and efficiency
Simple Multigraph Convolution Networks Previous methods PGCN MGCN MIMO-GCN
Simple Multigraph Convolution Networks Build Credible Graph Subgraph-level Edge-level Edge voting from multigraph
SMGCN Experiments 5
Thank You Here are our codes https://github.com/frinkleko/SMGCN 6
