Abstract: With the advent of deep learning, various deep neural network architectures have been proposed to capture the complex spatio-temporal dependencies in traffic data. This paper introduces a ...

Abstract: We investigate the utility of graph neural networks (GNNs) as proxies of power grid operational decision-making algorithms (optimal power flow (OPF) and security-constrained unit commitment ...