Patricia M. West, Patrick L. Brockett, Linda L. Golden, A Comparative Analysis of Neural Networks and Statistical Methods for Predicting Consumer Choice, Marketing Science, Vol. 16, No. 4 (1997), pp.

The Data Science Lab Neural Network Quantile Regression Using C# Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of neural network quantile regression. The ...

VisualStudioMagazine: What inspired you do present a session on introducing neural networks using C#? McCaffrey: In addition to being practical and powerful prediction techniques, neural networks form ...

They have managed to build a neural network, use it to solve a tricky problem, and then capture its insights in a relatively simple five-part equation that human scientists can use and understand.

Artificial neural networks -- algorithms inspired by connections in the brain -- have 'learned' to perform a variety of tasks, from pedestrian detection in self-driving cars, to ...

Neural networks with several process layers are known as "deep" networks and are used for deep learning algorithms The success of neural networks for stock market price prediction varies.

Results from neural networks support the idea that brains are “prediction machines” — and that they work that way to conserve energy.

Metal additive manufacturing (AM) experiments are slow and expensive. Engineers are using physics-informed neural networks to predict the outcomes of complex processes involved in AM. The team ...