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Found 4 papers, 4 papers with code
Scaling Graph Neural Networks with Approximate PageRank
Graph neural networks (GNNs) have emerged as a powerful approach for solving many network mining tasks.
Examining COVID-19 Forecasting using Spatio-Temporal Graph Neural Networks
In this work, we examine a novel forecasting approach for COVID-19 case prediction that uses Graph Neural Networks and mobility data.
Pathfinder Discovery Networks for Neural Message Passing
Additional results from a challenging suite of node classification experiments show how PDNs can learn a wider class of functions than existing baselines.
TF-GNN: Graph Neural Networks in TensorFlow
TensorFlow-GNN (TF-GNN) is a scalable library for Graph Neural Networks in TensorFlow.
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