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Found 4 papers, 1 papers with code
Graph Learning-Convolutional Networks
Recently, graph Convolutional Neural Networks (graph CNNs) have been widely used for graph data representation and semi-supervised learning tasks.
Graph Diffusion-Embedding Networks
We present a novel graph diffusion-embedding networks (GDEN) for graph structured data.
Graph Laplacian Regularized Graph Convolutional Networks for Semi-supervised Learning
Recently, graph convolutional network (GCN) has been widely used for semi-supervised classification and deep feature representation on graph-structured data.
Temporal Coherent and Graph Optimized Manifold Ranking for Visual Tracking
To address this problem, we propose a novel unified temporal coherence and graph optimized ranking model for weighted patch representation in visual tracking problem.
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