The report titled "Technological Advances and Practical Applications of Knowledge Graphs in the Power Sector" by the ...

One powerful way to do this is through a routine called slow reveal graphs.

Recently, researchers introduced a new representation learning framework that integrates causal inference with graph neural networks—CauSkelNet, which can be used to model the causal relationships and ...

Abstract: Graph representation learning is a fundamental research theme and can be generalized to benefit multiple downstream tasks from the node and link levels to the higher graph level. In practice ...

Explore how Neo4j’s Infinigraph unifies analytical and transactional data, removing ETL bottlenecks to power next-gen GenAI ...

Abstract: Exploring drug-target binding affinity (DTA) is essential for drug discovery. Numerous works rely on the one-dimensional SMILES representation of drugs for predicting drug-target affinity, ...

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

Dominion Energy is proposing a rate increase for residential customers that will add $10.51 a month starting in 2027. The State Corporation Commission, which held its first hearing about the possible ...

COLUMBUS, Ohio (WCMH) — The Public Utilities Commission of Ohio rejected a bid from Amazon, Google and others to overturn AEP’s new tariff, or rate structure, specifically for data centers. Amazon and ...

A galaxy proto-supercluster was discovered using VIMOS instrument of ESO’s Very Large Telescope. The astronomers who discovered it have nicknamed the bohemoth “Hyperion.” It has been visualized here.

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 ...