AZoM

AI Uses Crystal Symmetry to Find New Antiferromagnets for Spintronics

CDVAE, a symmetry-aware generative AI framework that embeds space-group information into the generation of crystal structures ...
IEEE

Dual Encoder-Based Dynamic-Channel Graph Convolutional Network With Edge Enhancement for Retinal Vessel Segmentation

Abstract: Retinal vessel segmentation with deep learning technology is a crucial auxiliary method for clinicians to diagnose fundus diseases. However, the deep learning approaches inevitably lose the ...
Semiconductor Engineering

Using Graph Attention for Virtual Metrology in Semiconductor Manufacturing (Intel Foundry, ASU)

Researchers from Arizona State University and Intel Foundry have published “Graph Attention-Based Virtual Metrology for Film Deposition Processes in Semiconductor Manufacturing”. Abstract “Artificial ...
Nature

Research on traffic flow prediction of progressive graph convolutional networks based on spatio-temporal self-attention mechanism

Traffic flow forecasting is a cornerstone of Intelligent Transportation Systems (ITS), aiming to infer future traffic states from historical observations to support congestion mitigation, route ...
Microsoft

Graph Convolutional Matrix Completion

We consider matrix completion for recommender systems from the point of view of link prediction on graphs. Interaction data such as movie ratings can be represented by a bipartite user-item graph with ...
Scientific Research Publishing

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ()

Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex dependencies ...
Ars Technica

Why do LLMs make stuff up? New research peers under the hood.

One of the most frustrating things about using a large language model is dealing with its tendency to confabulate information, hallucinating answers that are not supported by its training data. From a ...
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 ...
Nature

SEGCN: a subgraph encoding based graph convolutional network model for social bot detection

With the rapid development of Internet technology, cybersecurity incidents in cyberspace are frequent and have a great impact. Countries around the world regard network security situation awareness as ...