Devdiscourse

How AI is reshaping UAV cybersecurity and where it falls short

The study, titled Artificial Intelligence Methods for Unmanned Aerial Vehicles Cybersecurity: A Comprehensive Survey and ...
Scientific Research Publishing

A Review of Data-Driven Prediction of Undesirable Events in Offshore Oil Wells

The production and operation of offshore oil wells present typical characteristics of strong coupling, high nonlinearity, obvious time-varying behavior, and high operational risks. The occurrence of ...
News-Medical.Net

Graph neural networks accelerate drug discovery for complex bone diseases

Announcing a new publication for Acta Materia Medica journal. Traditional Chinese medicine has shown therapeutic potential in ...
EDN

GPUs: A high-throughput architecture confronting a workload shift

Frontier LLMs are evolving away from the dense and homogeneous AI workloads that originally favored GPU architectures.
GitHub

Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

The code in this repository implements an efficient generalization of the popular Convolutional Neural Networks (CNNs) to arbitrary graphs, presented in our paper: Michaël Defferrard, Xavier Bresson, ...
Voria

From Byzantine hymns to smart embryos: Four AI breakthroughs made in Thessaloniki

Four innovative artificial intelligence applications developed by departments at Aristotle University of Thessaloniki across ...
Frontiers

DEG-BRIN-GCN: interpretable graph convolutional framework with differentially expressed genes brain region interaction network prior for AD diagnosis

Due to the intricate dynamic coupling between molecular networks and brain regions, early diagnosis and pathological mechanism analysis of Alzheimer's disease (AD) remain highly challenging. To ...
The New York Times

Big Tech Wants Direct Access to Our Brains

As neural implant technology and A.I. advance at breakneck speeds, do we need a new set of rights to protect our most intimate data — our minds? Credit...Photo illustration by Tyler Comrie Supported ...
IEEE

Multigranularity Deep Graph Convolutional Neural Network Node Clustering Leveraging Spatial Information

Abstract: In the era of information explosion, clustering analysis of graph-structured data and empty graph-structured data is of great significance for extracting the intrinsic value of data. From ...