Understand the merits of large language models vs. small language models, and why knowledge graphs are the missing piece in ...

I spent almost two years after I left the Cyber Protection Brigade working on training. Not traditional military training ...

Embrace city science as a vital partner in architecture, merging creativity with data to build resilient and equitable urban ...

Salt Lake City is looking to update its oldest-lasting community plan, creating a new plan that aligns with current needs of ...

I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein function prediction is essential for elucidating biological processes and ...

Mitsui OSK Lines and Karadeniz Holding have extended their long-standing LNG-to-power partnership into a new arena, to develop what they describe as the world’s first integrated floating data centre ...

Add a description, image, and links to the graph-data-structure topic page so that developers can more easily learn about it.

Abstract: Graph neural network is a new neural network model in recent years, whose advantage lies in processing graph structure data. In the era of big data, people can collect a large amount of ...

High sparse Knowledge Graph is a key challenge to solve the Knowledge Graph Completion task. Due to the sparsity of the KGs, there are not enough first-order neighbors to learn the features of ...