Dynamic graph algorithms and data structures represent a vital research frontier in computer science, underpinning applications from network analysis to real-time system monitoring.

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 ...

Description The design, implementation, and analysis of abstract data types, data structures and their algorithms. Topics include: data and procedural abstraction, amortized data structures, trees and ...

A research team led by Bing Qin introduces a novel method for Knowledge Graph Completion using higher-order neighbor subgraphs to address sparsity issues, demonstrating its effectiveness in a ...

The rise of graph databases is closely related to AI's demand for data processing. AI technology requires vast amounts of structured and unstructured data, which must not only be input into ...

A set of independence statements may define the independence structure of interest in a family of joint probability distributions. This structure is often captured by a graph that consists of nodes ...

DTSA 5502 Trees and Graphs: Basics DTSA 5503 Dynamic Programming, Greedy Algorithms - Same as CSCA 5414 Total: 3 credits Want to learn more? Click the button below to watch the Data Science ...

Graphs -- data structures that show the relationship among objects -- are highly versatile. It's easy to imagine a graph depicting a social media network's web of connections. But graphs are also ...