FIT-GNN applies graph coarsening during inference to deliver orders-of-magnitude faster single-node inference and lower memory use on node and graph classification/regression tasks while keeping competitive accuracy.
Layer- dependent importance sampling for training deep and large graph convolutional networks
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FIT-GNN: Faster Inference Time for GNNs that 'FIT' in Memory Using Coarsening
FIT-GNN applies graph coarsening during inference to deliver orders-of-magnitude faster single-node inference and lower memory use on node and graph classification/regression tasks while keeping competitive accuracy.