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Found 3 papers, 2 papers with code
Top-Down Network Combines Back-Propagation with Attention
For example, during multi-task learning, the same top-down network is being used for both learning, via propagating feedback signals, and at the same time also for top-down attention, by guiding the bottom-up network to perform a selected task.
Topological based classification using graph convolutional networks
First, we show that even in the absence of any external information on nodes, a good accuracy can be obtained on the prediction of the node class using either topological features, or using the neighbors class as an input to a GCN.
Regional based query in graph active learning
As such, the uncertainty in the class of a node's neighbor may be a more appropriate selection criterion.
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