To address these limitations, we introduce a novel framework: the Molecular Merged Hypergraph Neural Network (MMHNN). MMHNN ...

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.

The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the ...

We’re told neural networks ‘learn’ the way humans do. A neuroscientist explains why that’s not the case — and why AI can't think like us yet.

Google, though, trained a neural network with lots of carefully labeled imagery that helped it learn how to distinguish facial features -- eyes, hair, glasses, mouths and so on -- from everything ...

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 ...

Algorithm optimization on Windows and Web, allowing the neural network to monitor every other frame instead of each of them; Improved anti-jitter algorithms that demand less resources from the device.