Researchers at the Institute of Science Tokyo have developed a neural-network-based 3D imaging technique that can precisely ...

The ability to analyze the brain's neural connectivity is emerging as a key foundation for brain-computer interface (BCI) ...

The Navier–Stokes partial differential equation was developed in the early 19th century by Claude-Louis Navier and George ...

A Cornell research group led by Prof. Peter McMahon, applied and engineering physics,has successfully trained various physical systems to perform machine learning computations in the same way as a ...

Numenta, the Silicon Valley artificial intelligence firm founded by Palm Pilot creator Jeff Hawkins, has been able to achieve a dramatic speed up in conventional neural networks using Xilinx ...

Neural networks are distributed computing structures inspired by the structure of a biological brain and aim to achieve cognitive performance comparable to that of humans but in a much shorter time.

The Defense Advanced Research Projects Agency awarded Professor Jie Gu and co-PIs from the University of Minnesota and Duke University up to $3.8 million through the Scalable Analog Neural-networks ...

Researchers applied the mathematical theory of synchronization to clarify how recurrent neural networks (RNNs) generate predictions, revealing a certain map, based on the generalized synchronization, ...

Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...