Abstract: Temporal graph learning aims to generate high-quality representations for graph-based tasks with dynamic information, which has recently garnered increasing attention. In contrast to static ...

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 ...