This paper develops fundamental limits of deep neural network learning by characterizing what is possible if no constraints are imposed on the learning algorithm and on the amount of training data.

Deep neural networks (DNNs) are a class of artificial neural networks (ANNs) that are deep in the sense that they have many layers of hidden units between the input and output layers. Deep neural ...

This example shows how to build and train a convolutional neural network (CNN) from scratch to perform a classification task with an EEG dataset.

The suspension system in a vehicle plays an important role in ensuring user comfort and safety by dampening vibrations from uneven road surfaces, maintaining vehicle stability, and ensuring contact ...

Researchers have developed a new tool, bimodularity, that adds directionality to community detection in networks.

Photo: Amazon Neural networks aren’t the only game in artificial intelligence, but you’d be forgiven for thinking otherwise after the hot streak sparked by ChatGPT’s arrival in 2022.