Physical-layer secret key generation (PSKG) is a well-known and effective method for boosting wireless security in the Internet of Things (IoT). This technique creates cryptographic keys from ...

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

Bio-Digital Catalyst Design: Generative Deep Learning for Multi-Objective Optimization and Chemical Insights in CO 2 Methanation ...

ChatGPT’s Deep Research tool acts as a research assistant and can quickly find great sources on a variety of topics.

Image generators are designed to mimic their training data, so where does their apparent creativity come from? A recent study suggests that it’s an inevitable by-product of their architecture.

The result is the world’s first deep learning exchange correlation (XC) functional, which achieves high accuracy without sacrificing speed. Microsoft’s new deep learning-powered DFT model has the ...

Mass spectrometry imaging (MSI) often suffers from inherent noise due to signal distribution across numerous pixels and low ion counts, leading to shot noise. This can compromise the accurate ...

A group of scientists led by researchers from the University of New South Wales (UNSW) in Australia has developed a novel deep-learning method for denoising outdoor electroluminescence (EL) images ...

Methodology: Introduction of the diffusion-scheduled denoising autoencoder (DDAE) that integrates diffusion noise scheduling into the denoising autoencoder framework. Representation: Extension of DDAE ...

A self-supervised deep learning model has been developed to improve the quality of dynamic fluorescence images by leveraging temporal gradients. The method enables accurate denoising without ...