A $1 million prize awaits anyone who can show where the math of fluid flow breaks down. With specially trained AI systems, ...
When a house catches on fire, we assume that a smoke alarm inside will serve one purpose and one purpose only: warn the ...
When a baby smiles at you, it's almost impossible not to smile back. This spontaneous reaction to a facial expression is part ...
The representation of individual memories in a recurrent neural network can be efficiently differentiated using chaotic recurrent dynamics.
A research team from the Institute of Modern Physics of the Chinese Academy of Sciences and Lanzhou University has obtained ...
Researchers in Japan built a miniature human brain circuit using fused stem-cell–derived organoids, allowing them to watch ...
Neuroscience continually strives to unravel the intricate relationship between neural network morphology, spiking dynamics, and their resulting functional ...
Abstract: The radial basis function neural network (RBFNN) is a learning model with better generalization ability, which attracts much attention in nonlinear system identification. Compared with the ...
Abstract: Optical neural networks (ONNs) have the potential to overcome scaling limitations of transistor-based systems due to their inherent low latency and large available bandwidth. However, ...
Representing the brain as a complex network typically involves approximations of both biological detail and network structure. Here, we discuss the sort of biological detail that may improve network ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein function prediction is essential for elucidating biological processes and ...
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