Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...

Neural network pruning is a key technique for deploying artificial intelligence (AI) models based on deep neural networks (DNNs) on resource-constrained platforms, such as mobile devices. However, ...

Dr. Jongkil Park and his team of the Semiconductor Technology Research Center at the Korea Institute of Science and Technology (KIST) have presented a new approach that mimics the brain's learning ...

A new paper examines the possible effects of two properties of receiver playing fields documented in studies of animal psychology -- habituation and neural adaptation -- on the efficacy of mate choice ...

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 tail end ...

NVIDIA's Vice President of Applied Deep Learning Research, suggest its potential evolution into a complete neural rendering system. In 2018, Cantanzaro introduced the idea that, in its advanced stages ...

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 ...