From the standpoint of neural network structures, the topology of neural circuits also plays a crucial role in information processing, with healthy neural networks exhibiting small world, scale-free, ...

A neural network is a series of algorithms that seek to identify relationships in a data set via a process that mimics how the human brain works.

The study introduces a method to analyze neural networks by mapping them onto graph structures, facilitating detailed analysis using network science principles. Neural network layers are represented ...

This provides a linear algebraic structure that enables us to extend desirable neural network structure to high dimensions with ease. Because of our strong algebraic foundation, we are able to express ...

Unlike previous models that suppressed neural activity to control signal flow, our model achieves routing by exciting different high-dimensional activity patterns through connectivity structure and ...

Neural Network Tutorial Using NumPy/TensorFlow/pytorch This repository contains a beginner-friendly tutorial on how to build a neural network from scratch using Python and the NumPy library. This ...

Computer-based neural networks can learn to do tasks. A new type of material, called a mechanical neural network, applies similar ideas to a physical structure.

Network traffic classification has been highly concerned by academia and industry for decades. In recent years, deep learning has attracted many scholars to use it in network traffic classification ...