IEEE

Autoencoder-Augmented Graph Neural Networks for Accurate and Scalable Structure Recognition in Analog/Mixed-Signal Schematics

Abstract: The increasing complexity of Analog/Mixed-Signal (AMS) schematics has been posing significant challenges in structure recognition, particularly in the intellectual property (IP) industry, ...

Novel AI platform accelerates discovery of chemical catalysts for industry

CatDRX is a generative AI framework developed at Institute of Science Tokyo, which enables the design of new chemical ...
AZoSensors

AI Maps Heat Inside Steelmaking’s Critical Sintering Process Beds

The Temporal Fusion Transformer model provides near-real-time insights into sintering temperatures, addressing critical ...
Devdiscourse

Fast and Accurate Water Leak Detection in Distribution Networks Using Deep Anomaly Models

Researchers from Politecnico di Milano propose a data-driven water leak detection method that treats leaks as anomalies in ...
eLife

High-Fidelity Neural Speech Reconstruction through an Efficient Acoustic-Linguistic Dual-Pathway Framework

This study presents a valuable advance in reconstructing naturalistic speech from intracranial ECoG data using a dual-pathway model. The evidence supporting the claims of the authors is solid, ...
Security Boulevard

Behavioral Analysis of AI Models Under Post-Quantum Threat Scenarios.

Explore behavioral analysis techniques for securing AI models against post-quantum threats. Learn how to identify anomalies and protect your AI infrastructure with quantum-resistant cryptography.
Albuquerque Journal

Sandia researchers build AI system to detect anomalies across the electrical grid

The electrical grid is a crucial, sometimes fragile, piece of infrastructure. As connectivity to the grid increases, so too does its vulnerability. Public Service Company of New Mexico, the state’s ...