Many intelligent applications and systems, including biomedical hardware and devices, require humancomputer interaction technology. This technology enables ...

A scientist combines attention neural networks with graph neural networks to better understand and design proteins. The approach couples the strengths of geometric deep learning with those of language ...

A neural network is better viewed as a collection of multiple optimisation processes, each with its own internal memory.

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...

Past psychology and behavioral science studies have identified various ways in which people's acquisition of new knowledge ...

A new framework that causes artificial neural networks to mimic how real neural networks operate in the brain has been ...

In 1890, psychologist William James described attention as the spotlight we shine not only on the world around us, but also on the contents of our minds. Most cognitive scientists since then have ...

Researchers from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences have developed a neural network model based on self-attention mechanisms to rapidly predict radiation ...

The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the tail end ...

WASHINGTON, August 29, 2023 – With their intricate arrangements and dynamic functionalities, proteins perform a plethora of biological tasks by employing unique arrangements of simple building blocks ...