The ability to analyze the brain's neural connectivity is emerging as a key foundation for brain-computer interface (BCI) ...

Information Theory Meets Deep Neural Networks: Theory and Applications. The previous volume can be viewed here: Volume I Deep Neural Networks (DNNs) have become one of the most popular research ...

A major AI architecture. A neural network is employed for many pattern recognition applications; however, its most popular use is the creation of language models used by ChatGPT, Gemini and other ...

Transformers are a neural network (NN) architecture, or model, that excels at processing sequential data by weighing the ...

A topic that's often very confusing for beginners when using neural networks is data normalization and encoding. Because neural networks work internally with numeric data, binary data (such as sex, ...

Qing Wei and colleagues from the College of Engineering, China Agricultural University, systematically elaborated on the ...

A regression problem is one where the goal is to predict a single numeric value. For example, you might want to predict the annual income of a person based on their sex, age, state where they live and ...

A new study suggests that the communication patterns within the brains of individuals with Alzheimer’s disease are less ...