The Heisenberg uncertainty principle puts a limit on how precisely we can measure certain properties of quantum objects. But researchers may have found a way to bypass this limitation using a quantum ...

Intelligent Systems course project (MSc in Computer Engineering @ Unversity of Pisa). Design and development of a MLP, RBF networks and Fuzzy System to estimate person's affective state. Design, ...

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

Abstract: The study presents the application of Artificial Neural Networks (ANNs) for pattern recognition, modeling, and analyzing their performance using MATLAB. Two neural architectures are compared ...

Listen to the first notes of an old, beloved song. Can you name that tune? If you can, congratulations — it’s a triumph of your associative memory, in which one piece of information (the first few ...

The integration of neural network models in autonomous robotics represents a monumental leap in artificial intelligence and robotics. These models, mirroring the human brain's complexity and ...

Department of Chemistry, The University of Hong Kong, Hong Kong 999077, P. R. China ...

Abstract: This advanced tutorial explores some recent applications of artificial neural networks (ANNs) to stochastic discrete-event simulation (DES). We first review some basic concepts and then give ...

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...