Tech Xplore

Reinforcement learning accelerates model-free training of optical AI systems

Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
Tech Xplore

No-code machine learning development tools

Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited ...

Self-Driving Cars Can’t See Without Their Eyes

My short film above, “Their Eyes,” spotlights the invisible, human work behind A.I. In it I explore the daily lives of ...
United States Army

Army establishes new AI, machine learning career path for officers

The U.S. Army has established a new career pathway for officers to specialize in artificial intelligence and machine learning (AI/ML), ...
Communications of the ACM

Hidden Engineering Behind Making AI Interpreters Work

Live AI interpreters must grasp meaning, tone, and intent even when sentences unfold slowly or indirectly. Languages differ ...

Interpretable neural networks help reveal the nature of dark matter

A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an interpretable artificial intelligence (AI) framework named Convolutional Kolmogorov ...
AZoSensors on MSN

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 challenges in steelmaking processes.
IEEE

Learning Causal Representations Based on a GAE Embedded Autoencoder

Abstract: Traditional machine-learning approaches face limitations when confronted with insufficient data. Transfer learning addresses this by leveraging knowledge from closely related domains. The ...
Frontiers

VAE deep learning model with domain adaptation, transfer learning and harmonization for diagnostic classification from multi-site neuroimaging data

In large public multi-site fMRI datasets, the sample characteristics, data acquisition methods, and MRI scanner models vary across sites and datasets. This non-neural variability obscures neural ...
Scientific Research Publishing

Traffic Speed Prediction Based on Autoencoder and Deep Learning ()

Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction model ...
GitHub

Enhancing EV Cost Prediction Using AutoEncoder-Based Feature Learning

Electric Vehicle (EV) cost prediction involves analyzing complex, high-dimensional data that often contains noise, multicollinearity, and irrelevant features. Traditional regression models struggle to ...