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

Transformers are a neural network (NN) architecture, or model, that excels at processing sequential data by weighing the ...

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

By implementing an automated 3D cell segmentation process, researchers mapped neurons and muscle fibers at the single-cell ...

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

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. This article dives into the happens-before ...

Qing Wei and colleagues from the College of Engineering, China Agricultural University, systematically elaborated on the ...

Machine learning and neural nets can be pretty handy, and people continue to push the envelope of what they can do both in high end server farms as well as slower systems. At the extreme end of the ...

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 ...

We talk a lot about AI, machine learning, and neural nets, but what's a neural net in the first place? Share on Facebook (opens in a new window) Share on X (opens in a new window) Share on Reddit ...

A new study suggests that the communication patterns within the brains of individuals with Alzheimer’s disease are less ...