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Search results with tag "Graphsage"
View-GCN: View-Based Graph Convolutional Network for 3D ...
openaccess.thecvf.comgraph, e.g., GCN in [29], GraphSAGE [18]. Graph at-tention network [49] uses attention to specify different weights to different nodes in neighborhood. Message pass-ing network [16] is based on edge embedding to cumulate messages from neighboring nodes for updating node fea-tures.
![Pietro Lio` arXiv:1710.10903v3 [stat.ML] 4 Feb 2018](/cache/preview/6/9/b/8/0/d/4/8/thumb-69b80d48100630b31293189afc348f88.jpg)
Pietro Lio` arXiv:1710.10903v3 [stat.ML] 4 Feb 2018
arxiv.orgtion of CNN architectures to graphs. More recently, Hamilton et al. (2017) introduced GraphSAGE, a method for computing node representations in an inductive manner. This technique operates by sampling a fixed-size neighborhood of each node, and then performing a specific aggregator over
![arXiv:1706.02216v4 [cs.SI] 10 Sep 2018](/cache/preview/9/a/6/8/0/7/1/d/thumb-9a68071d73afd8997ff3a74956baa9eb.jpg)
arXiv:1706.02216v4 [cs.SI] 10 Sep 2018
arxiv.orgFigure 1: Visual illustration of the GraphSAGE sample and aggregate approach. recognize structural properties of a node’s neighborhood that reveal both the node’s local role in the