总体而言，《IEEE Transactions on Neural Networks and Learning ...

Robot perception and cognition often rely on the integration of information from multiple sensory modalities, such as vision, ...

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 ...

The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...

In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

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

Researchers at The Hong Kong University of Science and Technology (HKUST) School of Engineering have developed a novel ...

A Neural Engine, specifically Apple’s Neural Engine (ANE), is a specialized hardware component designed to accelerate machine learning tasks on Apple devices. Introduced with the iPhone X and the A11 ...

LAUSANNE, Switzerland--(BUSINESS WIRE)--Neural Concept, the leading Engineering Intelligence platform that transforms product design with 3D Deep Learning, has announced that it has raised $27 million ...