Networks of neurons can perform computations that have proved very difficult to emulate in conventional computers. In trying to understand how real nervous systems achieve their remarkable ...

This can be done analytically in linear regression, but there is no analytical solution in a feed-forward neural network with hidden units. In back-propagation, the weights and thresholds are ...

A Generative Adversarial Network (GAN) is a type of machine learning model that’s used to generate fake data that resembles ...

Below are strategies for cutting through the noise—by facing hard questions head-on rather than deferring them.

The seven decades of "artificial intelligence" have been marked by exaggerated promises, surprising developments and ...

Professor Se-Bum Paik's research team in the Department of Brain Cognitive Sciences solved the weight transport problem, a long-standing challenge in neural network learning, and through this ...

More information: Adityanarayanan Radhakrishnan et al, Mechanism for feature learning in neural networks and ...