Blending ‘old-fashioned’ logic systems with the neural networks that power large language models is one of the hottest trends ...

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 ...

The Lorenz attractor is an example of complex dynamical systems. Two neuroscientists have discovered a way to learn complex ...

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...

Deep neural networks can perform wonderful feats thanks to their extremely large and complicated web of parameters. But their complexity is also their curse: The inner workings of neural networks are ...

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, ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

A deep neural network (DNN) is a system that is designed similar to our current understanding of biological neural networks in the brain. DNNs are finding use in many applications, advancing at a fast ...