In this paper, we propose STGAMAM, which integrates Spatial-Temporal fusion Graph neural networks with a novel Adjacency Matrix and self-Attention Mechanisms to capture both long-term temporal ...

I have calculated an "influence score" on an unweighted and weighted graph. I used BFS algorithm for the unweighted graph and Dijkstra's algorithm for the weighted graph.

For this, we integrate the concept of polytopic uncertainty into existing approaches that learn graph Laplacians and adjacency matrices, constraining the solution space to a polytopic set. Our ...

This can be solved partially by making separate adjacency matrices for different segments of the incidence matrix, but the choice for the size of the segments is always arbitrary, and information ...