Deep learning models go above and beyond traditional machine learning and can process data and recognize patterns much more efficiently.

However, it should be noted that deep learning as a black-box model, its ability is explored through a large number of experiments. The theory of deep learning has gradually attracted the attention of ...

This repository contains implementations (mostly in PyTorch), relevant resources and lessons related to information theory of deep learning. The aim is to have a single source for all the information ...

Effective learning isn't just about finding the easiest path—it's about the right kind of challenge. Two prominent theories—Desirable Difficulties (DDF) and Cognitive Load Theory (CLT)—offer ...

Despite promising advances, the opaque nature of deep learning models makes it difficult to interpret them, which is a drawback in terms of their practical deployment and regulatory compliance. Deep ...

Deep Reinforcement Learning for Wireless Communications and Networking presents an overview of the development of DRL while providing fundamental knowledge about theories, formulation, design, ...