Abstract: Temporal graph learning aims to generate high-quality representations for graph-based tasks ... Extensive experiments demonstrate that the proposed model S2T achieves at most 10.13% ...

Here we develop a model for shortening coverage paths in arbitrary environments using grid-based methods, which redefines the path optimization problem as finding the largest Hamiltonian sub-graph of ...