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 ...
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, ...
AlphaGalileo

KAIST, AI judges manufacturing beyond craftsmanship and language barriers

Most of the plastic products we use are made through injection molding, a process in which molten plastic is injected into a mold to mass-produce ...
Mirage News

KAIST AI Transcends Craft and Language in Manufacturing

Most of the plastic products we use are made through injection molding, a process in which molten plastic is injected into a mold to mass-produce ...
Security Boulevard

AI-Driven Anomaly Detection in Post-Quantum Context Streams

Discover how AI-driven anomaly detection safeguards post-quantum context streams in Model Context Protocol (MCP) environments, ensuring robust security for AI infrastructure against future threats.
IEEE

Uncorrelated Sparse Autoencoder With Long Short-Term Memory for State-of-Charge Estimations in Lithium-Ion Battery Cells

Abstract: For the safe and reliable operation of battery-driven machines, accurate state-of-charge (SOC) estimations are necessary. Unfortunately, existing methods often fail to identify patterns ...
GitHub

Video Autoencoder: self-supervised disentanglement of 3D structure and motion

@inproceedings{Lai21a, title={Video Autoencoder: self-supervised disentanglement of 3D structure and motion}, author={Lai, Zihang and Liu, Sifei and Efros, Alexei A and Wang, Xiaolong}, ...
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, ...