"We studied the simplest model for this transfer learning approach and developed a mathematical theory for networks with one hidden layer," says Ingrosso. Innovative combination of analytical methods ...

Researchers have developed a transfer learning-enhanced physics-informed neural network (TLE-PINN) for predicting melt pool morphology in selective laser melting (SLM). This novel approach ...

The process uses neural networks to apply the look and feel of one image to another, and appears in apps like Prisma and Facebook. These style transfers, however, are stylistic, not photorealistic.

Because the log-sigmoid function constrains results to the range (0,1), the function is sometimes said to be a squashing function in neural network literature. It is the non-linear characteristics of ...

For decades, scientists have looked to light as a way to speed up computing. Photonic neural networks—systems that use light ...

Researchers from the University of Tokyo in collaboration with Aisin Corporation have demonstrated that universal scaling ...

An Alternative to Conventional Neural Networks Could Help Reveal What AI Is Doing behind the Scenes. ... the question of which functions a neural network can represent arises.

Modeled on the human brain, neural networks are one of the most common styles of machine learning. Get started with the basic design and concepts of artificial neural networks.

Mohamad Hassoun, author of Fundamentals of Artificial Neural Networks (MIT Press, 1995) and a professor of electrical and computer engineering at Wayne State University, adapts an introductory ...