The GSQL Graph Algorithm Library is a collection of high-performance GSQL queries, each of which implements a standard graph algorithm. Each algorithm is ready to be installed and used, either as a ...

Abstract: The graph classification problem is learning to classify separate, individual graphs in a graph database into two or more categories. A number of algorithms have been introduced for the ...

We propose a simple and fast algorithm based on the spectral decomposition of graph Laplacian to perform graph classification and get a first reference score for a dataset. We show that this method ...

Abstract: We present in this paper a graph classification approach using genetic algorithm and a fast dissimilarity measure between graphs called graph probing. The approach consists in the learning ...

Both methods can be implemented using a stack or a queue, respectively. One of the most common problems in graph algorithms is finding the shortest path between two nodes, which means finding the ...

We use different dropout ratios (0.1–0.5) on the two graph node classification data sets of Cora and Citeseer, and conduct experiments on the neural network based on the LGNN4 algorithm to compare and ...

Computer scientists are abuzz over a fast new algorithm for solving one of the central ... have meekly succumbed to categorization as either hard or easy, graph isomorphism has defied classification.

As a deep learning expert, I emphasize the importance of image-to-graph conversion for applying GNNs to image classification. Segmentation algorithms can identify regions of interest, creating ...

A new algorithm efficiently solves the graph isomorphism problem, computer scientist László Babai announced November 10 at a Combinatorics and Theoretical Computer Science seminar at the ...

For decades computer scientists had been trying to develop a fast algorithm for determining when it’s possible to add edges to a graph so that it remains “planar,” meaning none of its edges cross each ...