Abstract: Problems such as bisection, graph coloring, and clique are generally believed hard in the worst case. However, they can be solved if the input data is drawn randomly from a distribution over ...

Random geometric graphs (RGGs) are commonly used to model networked systems that depend on the underlying spatial embedding. We concern ourselves with the probability distribution of an RGG, which is ...

Trinity is a general purpose distributed graph system over a memory cloud. Memory cloud is a globally addressable, in-memory key-value store over a cluster of machines. Through the distributed ...

Much work has been devoted to supporting RDF data. But state-of-the-art systems and methods still cannot handle web scale RDF data effectively. Furthermore, many useful and general purpose graph-based ...

GAT-RWOS is a graph-based oversampling method that combines Graph Attention Networks (GATs) with random walk-based oversampling to address the class imbalance problem. By utilizing GAT's attention ...

Bahmani A, Li G, Willett TL, Montesano J. Three-dimensional microscopic assessment of randomly distributed representative volume elements for high fiber volume fraction unidirectional composites.

A sui generis, multi-model open source database, designed from the ground up to be distributed. ArangoDB keeps up with the times and uses graph, and machine learning, as the entry points for its ...