Neural networks have emerged as a powerful framework for addressing complex problems across numerous scientific domains. In particular, the interplay between neural network models and constraint ...

Lab-grown brain tissue learned to balance a virtual pole with 46% accuracy, revealing how living neural networks adapt and ...

A Queen’s research team has developed a new way to train AI systems so they focus on the bigger picture instead of specific, ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known ...

Article reviewed by Grace Lindsay, PhD from New York University. Scientists design ANNs to function like neurons. 6 They write lines of code in an algorithm such that there are nodes that each contain ...

Researchers generated images from noise, using orders of magnitude less energy than current generative AI models require.

RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

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