Our study uses Graph Neural Networks (GNNs) to enhance discrete-time survival predictions (GNN-surv) by leveraging relationships in these networks. We build these networks using cancer patients' ...

Abstract: Recently, a variety of time-varying graphs, such as space-time graph and event-driven graph, are widely employed for modelling the dynamic topologies of satellite Disruption-Tolerant ...

Abstract: Variations of target appearances due to illumination changes, heavy occlusions, and target deformations are the major factors for tracking drift. In this paper, we show that the tracking ...