Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

Innovations addressing some of the world’s most pressing challenges took centre stage at the Innovator Meet Tech Exhibition ...

Researchers developed a terahertz imaging platform that uses deep learning to separate chemical signatures from noise. The ...

As sensor data overwhelms the cloud, Innatera’s neuromorphic chips bring always-on, ultra-low-power AI directly to the edge. But how?

During his more than two decades with Nvidia, Rev Lebaredian has had a ringside seat to the show that has been the evolution of modern AI, from the ...

Microgrids play a growing role in modern power systems, supporting renewable integration, local resilience, and decentralized energy management. Yet as renewable penetration rises, maintaining stable ...

Hybrid climate modeling has emerged as an effective way to reduce the computational costs associated with cloud-resolving ...

A research team led by Professor Wang Hongzhi from the Hefei Institute of Physical Science of the Chinese Academy of Sciences has developed a multi-stage, dual-domain, progressive network with ...

Researchers at the Department of Energy's Oak Ridge National Laboratory have developed a deep learning algorithm that ...

South Korean researchers have developed a guided-learning framework that accurately predicts PV power without requiring irradiance sensors during operation, using routine meteorological data instead.

A research team from the Xi'an Institute of Optics and Precision Mechanics (XIOPM) of the Chinese Academy of Sciences, along with collaborators from the Institute National de la Recherche Scientifique ...