Neuroscientists want to understand how individual neurons encode information that allows us to distinguish objects, like ...

In recent years, with the public availability of AI tools, more people have become aware of how closely the inner workings of ...

Predicting how molecular changes affect the brain's overall activity is a major challenge in neuroscience. Many deep ...

One of the most crucial and expensive parts of electricity transmission and distribution systems is power transformers. In power distribution and transmission networks, quickly diagnosing power ...

A new image compression technique is presented using hybrid neural networks that combine two different learning networks, the auto-associative multi-layer perceptron (AMLP) and the self-organizing ...

One of the main problems in the analysis of cavity systems is the necessity to construct special basis sets that meet boundary conditions. The task often involves variational optimization of ...

This paper introduces a novel graph neural layer, the dynamic connection layer (DCL), designed to address chemical graphs’ inaccurate atomic connection. The DCL layer employs a correction function, ...

This important study demonstrates the significance of incorporating biological constraints in training neural networks to develop models that make accurate predictions under novel conditions. By ...

Thanks to the neural network, the researchers now suspect, for example, that the black hole at the center of the Milky Way is spinning almost at top speed. Its rotation axis points to Earth.