Abstract: Rapidly accumulating, large-scale and long-term meteorological data provide unprecedented opportunities for data-driven meteorological models and fine-grained numerical weather prediction.

GraphSAINT is a general and flexible framework for training GNNs on large graphs. GraphSAINT highlights a novel minibatch method specifically optimized for data with complex relationships (i.e., ...

In this paper, we consider sparse inhomogeneous Erdős–Rényi random graph ensembles where edges are connected independently with probability pij. We assume that pij = 𝜀Nf (wi,wj), where (wi)i≥1 is a ...

//NOTE : This assumes that, we don't have cycle in the given directed graph. You can simply add few things in the same code to check for cycle also ...