AdaKernel learns adaptive kernel scale parameters inside GNNs for spatiotemporal data while preserving geometric structure, with experiments showing gains on kriging, imputation and forecasting tasks.
Nodetrans: A graph transfer learning approach for traffic prediction.arXiv preprint arXiv:2207.01301,
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AdaKernel: Learning Adaptive Kernel Parameters for Spatiotemporal Graph Neural Networks
AdaKernel learns adaptive kernel scale parameters inside GNNs for spatiotemporal data while preserving geometric structure, with experiments showing gains on kriging, imputation and forecasting tasks.