Physicists develop new protocol for building photonic graph states

Physicists have long recognized the value of photonic graph states in quantum information processing. However, the difficulty ...
Frontiers

Multi-modal Learning with Large-scale Models

Robot perception and cognition often rely on the integration of information from multiple sensory modalities, such as vision, ...
Coordinated Science Laboratory

Streaming the Future: How Neural Networks Are Transforming Video Streaming Technology

University of Illinois professor Klara Nahrstedt received $275,000 from the National Science Foundation to develop streaming ...
Frontiers

Signal Processing for Representation Learning: Theoretical Foundations and Emerging Applications

Representation learning lies at the core of modern artificial intelligence, enabling neural networks to uncover meaningful, ...
EurekAlert!

PolyU develops novel AI graph neural network models to unravel interdisciplinary complexities in image recognition and neuroscience

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...
Hosted on MSN

Top uses and applications of neural networks

The curious minds at ColdFusion explore how neural networks are shaping today’s AI applications. Tom Homan’s bid for Minnesota reset begins with series of demands Yankees add former player to ...
Tech Xplore

New graph attention network models higher-order relationships in complex graph data

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
GitHub

ML SDK Scenario Runner

The Scenario Runner is an application that executes shader and neural network graph workloads through Vulkan® or the ML extensions for Vulkan®. The Scenario Runner acts as a validation and performance ...
IEEE

Graph Neural Network-Driven Networking for Robust Industrial Wireless Sensor Networks

Abstract: Industrial wireless sensor networks (IWSNs) play a critical role in enabling real-time monitoring and intelligent automation in modern industrial applications. However, maintaining reliable ...
IEEE

Overview of Graph Neural Networks Application on State-of-the-Art Cyber Security Network Threat Detection Techniques

Detecting anomalies and threats in computer networks has been a center of cyber-security research for quite some time [1] and gaining popularity as new attack and defense techniques were made possible ...
C&EN

End-to-End Modeling of Reaction Field Energy Using Data-Driven Geometric Graph Neural Networks

Electrostatic interactions are fundamental to the structure, dynamics, and function of biomolecules, with broad applications in protein–ligand binding, enzymatic catalysis, and nucleic acid regulation ...