These utility functions are ideal for demonstration as they comprise a number of different graph-based subproblems, and thus demonstrate the usefulness of our method over a wide range.

Knowledge graph embedding is an effective way to represent knowledge graph, which greatly enhance the performances on knowledge graph completion tasks, e.g., entity or relation prediction. For ...

Introduction Paternal prepubertal passive smoke exposure may increase the risk of childhood asthma. However, its association ...

Infinigraph is a new distributed graph architecture that allows Neo4j’s database to run operational and analytical workloads ...

Experimental device harnesses quantum properties for efficient processing at room temperature. Engineers are working to ...

For a long time, companies have been using relational databases (DB) to manage data. However, with the increasing use of large AI models, integration ...

However, while ClickUp offers a lot, its numerous add-ons can get pricey, and some of its advanced features fall short of ...

As urbanisation and industrial activity continue to expand, noise and vibration pollution are becoming increasingly critical ...

PFIX provides convex exposure to rising long-term rates via payer swaptions, making it a strong hedge in volatile, steepening ...

Gamez, a gynecologic oncologist at the Mayo Clinic in Minnesota, has revealed the four subtle symptoms of a 'silent' cancer ...

The rise of memecoins proves that attention is the most valuable commodity in crypto. Memecoins lower the barriers to entry in crypto by wrapping speculation ...