Temporal Graph Neural Networks for Irregular Data

Joel Oskarsson, Per Sidén, Fredrik Lindsten

Abstract: This paper proposes a temporal graph neural network model for forecasting of graph-structured irregularly observed time series. Our TGNN4I model is designed to handle both irregular time steps and ...