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

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 ...

Intel is looking for a Data Scientist who specializes in Demand and Supply Planning to develop advanced analytics and machine learning systems that will optimiz ...

Dengue and chikungunya, the two mosquito-borne diseases that frequently circulate at the same time, share the same Aedes ...

A relatively simple statistical analysis method can more accurately predict the risk of landslides caused by heavy rain, ...

The threat to software-as-we-know-it comes from digital data: the foundational, eight-decades-long trend driving the ...

Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...

"Industry momentum further strengthened in December 2025 as the IIP rose by 7.8 per cent, reaching its highest level in over ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

India’s industrial production grew at an over two-year high pace of 7.8 per cent in December 2025 on the back of robust ...

The Kennedy College of Science, Richard A. Miner School of Computer & Information Sciences, invites you to attend a doctoral dissertation proposal defense by Nidhi Vakil, titled: "Foundations for ...

Nevertheless, scx_horoscope is a fully functional CPU scheduler that loads into the Linux kernel to decide your processor's ...