BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs ...

Other than giving us an appreciation how little difference going eight miles an hour over the speed limit makes, that ETA service is a remarkable invention — and one that takes a hell of a lot of ...

However, current artificial neural network circuit architectures do not fully embrace small-world neural network models. Here, we present the neuromorphic Mosaic: a non-von Neumann systolic ...

For instance, the application of NAS to Graph Neural Networks (GNNs) is explored in depth, with the authors discussing the unique challenges and opportunities presented by non-Euclidean data.

Recurrent neural networks, or RNNs, are a style of neural network that involve data moving backward among layers. This style of neural network is also known as a cyclical graph .

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 ...

A new technical paper titled “Machine Intelligence on Wireless Edge Networks” was published by researchers at MIT and Duke ...