Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited ...

In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...

Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test ...

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 ...

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...

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 ...

As artificial intelligence explodes in popularity, two of its pioneers have nabbed the 2024 Nobel Prize in physics. The prize surprised many, as these developments are typically associated with ...

Neural Concept aims to accelerate these timelines by integrating AI directly into CAD and physics-based simulation ...

A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an interpretable artificial intelligence (AI) framework named Convolutional Kolmogorov ...

Using lab-grown brain tissue, researchers uncovered complex patterns of neural signaling that differ subtly between healthy ...