Then, HestGCL designs spatial-aware and temporal-aware graph neural networks for spatial and temporal views, respectively. Finally, HestGCL uses the node representations obtained from each view ...

To capture complex non-linear correlations of loads, Wang et al. (2023) proposed spatial and temporal graph neural network for residential load prediction. The multiple dependence graphs consists of ...

To address the issue that existing wireless sensor network (WSN)-based anomaly detection methods only consider and analyze temporal features, in this article, a self-supervised learning-based ...

In a recent study posted to the bioRxiv* server, researchers demonstrated the feasibility of reproducing the previously observed spatial summation of pain (SSp) effect during the coronavirus ...

The spatial map of the simulated data consists of 500 voxels in a 2-dimensional matrix with 10 × 50 voxels (which can be conveniently divided into 5 sub-regions, each with a dimensionality of 10 × 10) ...

Study reveals spatial, temporal, and trend characteristics using ... and N = duration of summation of the precipitation. The mean EP is computed annually to represent the ... The results of plotted ...

It is therefore evident that Kenya has had extreme drought events whose spatial and temporal variability has not been understood, ... The SPEI graphs were used to categorize drought as per [19] , ...