As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

Researchers from the University of Tokyo in collaboration with Aisin Corporation have demonstrated that universal scaling laws, which describe how the properties of a system change with size and scale ...

Lightweight convolutional neural networks improved lung cancer classification accuracy in histopathological images while ...

For the first time, researchers at the Netherlands Institute for Neuroscience and Amsterdam UMC have identified what happens in neural networks deep within the brain during obsessive thoughts and ...

Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...

During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...

Deep neural networks (DNNs) have become a cornerstone of modern AI technology, driving a thriving field of research in ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting expertise.From neural networks to N ...

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

Both a wildfire and activity of digital “neurons” exhibit a phase transition from an active to an absorbing phase. Once a system reaches an absorbing phase, it cannot escape from it without outside ...