CoinTelegraph

An overview of graph neural networks (GNNs), types and applications

Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...
Forbes

How Network Graphs Connect The Dots In A World Of Ever-Expanding Data

You wouldn’t change up your entire production process based on sales from just a couple of locations, and you wouldn’t lower auto insurance premiums across the board because collision rates went down ...
Semiconductor Engineering

Physics Simulation With Graph Neural Networks Targeting Mobile

The demand for immersive, realistic graphics in mobile gaming and AR or VR is pushing the limits of mobile hardware. Achieving lifelike simulations of fluids, cloth, and other materials historically ...
NextBigFuture

Generalized Graph Networks ups Deep Learning to next level AI

Deep Learning and Machine Learning has made breakthroughs in recent years. There is tens of billions of dollars going into development of the new AI. Google and Deep Mind are recognizing that Deep ...
VentureBeat

LinkedIn creates PASS to tailor graph neural networks for social media

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Graphs are, quite simply, a universal ...
Semiconductor Engineering

Predicting Defect Properties In Semiconductors With Graph Neural Networks

A technical paper titled “Accelerating Defect Predictions in Semiconductors Using Graph Neural Networks” was published by researchers at Purdue University, Indian Institute of Technology (IIT) Madras, ...
CoinTelegraph

What is The Graph, and how does it work?

What is The Graph (GRT) cryptocurrency? The Graph is a decentralized indexing system that allows users to query data from blockchain networks, making DApp development easier. The Graph is an ...