A transfer learning approach applied to hybrid neural networks composed of classical and quantum elements. This repository contains the source code related to the research paper "Transfer learning in ...

However, in I have used a phenomenon called “quantum tunnelling” to design a neural network that can “see” optical illusions in much the same way humans do.

Neural networks can estimate the degree of entanglement in quantum systems far more efficiently than traditional techniques, a new study shows. By side-stepping the need to fully characterize quantum ...

A new computational method, based on neural networks, can simulate open quantum systems with unprecedented versatility.

We design a simple Quantum PINN to solve the one-dimensional Poisson problem using a Continuous Variable (CV) quantum computing framework. We discuss the impact of different optimizers, PINN residual ...

Russian physicists from NUST MISIS, the Russian Quantum Center and Lomonosov Moscow State University have presented a method for highly accurate classification of 4 classes of images. The technology ...

A quantum algorithm for training wide and deep classical neural networks Abstract Given the success of deep learning in classical machine learning, quantum algorithms for traditional neural network ...

A team of physicists has developed artificial neural networks to represent quantum systems.

With Python and NumPy getting lots of exposure lately, I'll show how to use those tools to build a simple feed-forward neural network.