7 Supplementary Material

Neural Information Processing Systems 

The sample explanatory features were fed into a multi-layer perceptron, then the learned latent features and sample spatial locations were fed into a Gaussian process model. GP variance is used as the uncertainty measure. We first constructed a spatial graph based on each sample's k-nearest-neighbor by spatial distance. The model contains two GCN layers. It contains a multi-level graph neural network to capture the long-range interactions among particles with linear complexity.

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