Small and dense but filled with vitally important neural fibers, the brainstem has been hard for brain imaging technologies ...

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 ...

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

AI became powerful because of interacting mechanisms: neural networks, backpropagation and reinforcement learning, attention, ...

Researchers at the Department of Energy’s Oak Ridge National Laboratory have developed a deep learning algorithm that analyzes drone, camera and sensor data to reveal unusual vehicle patterns that may ...

Researchers say that the recommendation algorithm published by X doesn't offer the kind of transparency that would actually ...

Abstract: Despite the wide variety of applications and use cases that can be solved with the help of machine learning algorithms, researchers have yet to develop a general artificial intelligence ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

A team of astronomers based at the European Space Agency demonstrated how artificial intelligence technology will alter existing methods of locating rare astronomical phenomena within our galaxy, the ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

Artificial intelligence and machine learning have transformed how we process information, make decisions, and solve complex problems. Behind every ...

The agent acquires a vocabulary of neuro-symbolic concepts for objects, relations, and actions, represented through a ...