Prasun Chaudhuri speaks to expert Subrata Das about the opportunities. Das is currently an adjunct faculty member at ...

Multilayer graphs are commonly used for representing different relations between entities and handling heterogeneous data processing tasks. Nonstandard multilayer graph clustering methods are needed ...

Mathematicians are interested in how infinite clusters form within infinite graphs, such as a square grid extending in all directions. In this setting, they observe something surprising: a phase ...

No commercial product was ever built, but the foundation was set for a 10-year transition, for Google, from a keyword-based search engine to an entity-based one.

From 0 to 300 rewires, the clustering algorithm could cluster all graphs correctly. At 400 rewires, it misplaced some graphs in some of the 100 repetitions, showing a mean Jaccard index lower than 1.

In graph signal processing (GSP), graph learning is concerned with the inference of an underlying graph best capable of modeling a dataset of graph signals. However, more complex datasets are derived ...