Graph neural networks, or GNNs, are a powerful technique that leverage the graph's connectivity and input features to make predictions about graphs. TF-GNN is a production-tested library for building GNNs at large scale. It supports both modeling and training in TensorFlow and provides tooling for subgraph sampling. GNNs can be
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GNNs: Making predictions for an object in contextBuilding GNN architecturesTraining orchestrationConclusionSort: