Dynamic graph algorithms and data structures represent a vital research frontier in computer science, underpinning applications from network analysis to real-time system monitoring. These methods ...
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New framework reduces memory usage and boosts energy efficiency for large-scale AI graph analysis
BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph partitioning, has been developed by researchers at the ...
In algorithms, as in life, negativity can be a drag. Consider the problem of finding the shortest path between two points on a graph — a network of nodes connected by links, or edges. Often, these ...
A professor has helped create a powerful new algorithm that uncovers hidden patterns in complex networks, with potential uses in fraud detection, biology and knowledge discovery. University of ...
Quantum computers promise to speed calculations dramatically in some key areas such as computational chemistry and high-speed networking. But they're so different from today's computers that ...
A puzzle that has long flummoxed computers and the scientists who program them has suddenly become far more manageable. A new algorithm efficiently solves the graph isomorphism problem, computer ...
Like the core algorithm, Google’s Knowledge Graph periodically updates. But little has been known about how, when, and what it means — until now. I believe these updates consist of three things: ...
Scalable Graph Algorithms for Bioinformatics using Structure, Parameterization and Dynamic Updates, ERC Consolidator Grant, 9/2025-8/2030 Sequencing technologies have developed to be cheap and ...
A couple of weeks ago, I attended and spoke at the first stop in the Neo4j GraphTour in Washington D.C. and I was able to get the best answer yet to a question that I’d been pondering: what’s the ...
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