A common objective for neural networks is to find a mathematical function, or curve, that best connects certain data points. The closer the network can get to that function, the better its predictions ...

Neural Architecture Search (NAS) is an emerging area focused on automating the design of neural network architectures. The overarching goal of NAS research is to discover optimal network ...

A new neural-network architecture developed by researchers at Google might solve one of the great challenges for large language models (LLMs): extending their memory at inference time without ...

Abstract “Deep neural network (DNN) inference on power-constrained edge devices is bottlenecked by costly weight storage and data movement. We introduce MIWEN, a radio-frequency (RF) analog ...