Nature

Neural Network Approximation Techniques

Neural network approximation techniques have emerged as a formidable approach in computational mathematics and machine learning, providing robust tools for approximating complex functions. By ...
Nature

Deep Learning and Neural Network Approximations

Deep learning has emerged as a transformative paradigm in modern computational science, leveraging neural networks to approximate complex functions across a variety of domains. Central to this ...
Visual Studio Magazine

Neural Network Activation Functions in C#

James McCaffrey explains what neural network activation functions are and why they're necessary, and explores three common activation functions. Understanding neural network activation functions is ...
Science Daily

Synchronization in neural nets: Mathematical insight into neuron readout drives significant improvements in prediction accuracy

Researchers applied the mathematical theory of synchronization to clarify how recurrent neural networks (RNNs) generate predictions, revealing a certain map, based on the generalized synchronization, ...
Scientific American

What is a neural network and how does its operation differ from that of a digital computer? (In other words, is the brain like a computer?)

Mohamad Hassoun, author of Fundamentals of Artificial Neural Networks (MIT Press, 1995) and a professor of electrical and computer engineering at Wayne State University, adapts an introductory section ...
Investopedia

Neural Networks Explained: Basics, Types, and Financial Uses

James Chen, CMT is an expert trader, investment adviser, and global market strategist. Andy Smith is a Certified Financial Planner (CFP®), licensed realtor and educator with over 35 years of diverse ...
Visual Studio Magazine

Neural Network Activation Functions in C#

Understanding neural network activation functions is essential whether you use an existing software tool to perform neural network analysis of data or write custom neural network code. This article ...