Neuroscientists have set up computer frameworks that can help model individual brain dynamics.

We humans excel at generalization. If you taught a toddler to identify the color red by showing her a red ball, a red truck and a red rose, she will most likely correctly identify the color of a ...

We humans excel at generalization. If you taught a toddler to identify the color red by showing her a red ball, a red truck and a red rose, she will ...

In a separate post, Behrouz claimed that based on internal testing on the BABILong benchmark (needle-in-a-haystack approach), ...

Researchers developed COMET, a deep learning framework that leverages electronic health records and omics data to improve ...

Two new neural network designs promise to make AI models more adaptable and efficient, potentially changing how artificial ...

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, ...

The Chinese Canadian artist is presenting a new kinetic work as part of the arts and culture programme at the 2025 World ...

This work models reinforcement-learning experiments using a recurrent neural network. It examines if the detailed credit assignment necessary for back-propagation through time can be replaced with ...

AI applications like ChatGPT are based on artificial neural networks that, in many respects, imitate the nerve cells in our ...

However, the neural networks—computer models inspired by the human brain—behind these ... Liboni et al, Image segmentation ...