The learning algorithm that enables the runaway success of deep neural networks doesn’t work in biological brains, but researchers are finding alternatives that could. In 2007, some of the leading ...

A new technical paper titled “Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware” was published by researchers at Purdue University, Pennsylvania State ...

A new theoretical framework argues that the long-standing split between computational functionalism and biological naturalism misses how real brains actually compute.

Research reveals why AI systems can't become conscious—and what radically different computing substrates would be needed to ...

FLAMeS, a new convolutional neural network, enhances MS lesion segmentation accuracy using only T2-weighted FLAIR images, ...

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 ...

It shows the schematic of the physics-informed neural network algorithm for pricing European options under the Heston model. ...