The field of machine learning is an interdisciplinary area that aims to extract useful
information from data through mathematical means. Integrating quantum computing with …

Quantum machine learning has established as an interdisciplinary field to overcome
limitations of classical machine learning and neural networks. This is a field of research …

This work presents a novel fundamental algorithm for for defining and training Neural
Networks in Quantum Information based on time evolution and the Hamiltonian. Classical …

Deep learning is one of the most successful and far-reaching strategies used in machine
learning today. However, the scale and utility of neural networks is still greatly limited by the …

Quantum computing is expected to fundamentally change computer systems in the future.
Recently, a new research topic of quantum computing is the hybrid quantum–classical …

Hybrid Quantum-Classical Machine Learning (ML) is an emerging field, amalgamating the
strengths of both classical neural networks and quantum variational circuits on the current …

The unprecedented progress in the domain of quantum computing in the last few years has
influenced researchers around the globe to solve multitudes of problems in this promising …

Quantum machine learning is emerging as a strategy to solve real‐world problems. As a
quantum computing model, parameterized quantum circuits provide an approach for …

In our constantly evolving world, an overwhelming influx of data permeates every moment—
be it daily, hourly, or even by the second. We communicate, share links, images, and …

Quantum computers promise improving machine learning. We investigated the performance
of new quantum neural network designs. Quantum neural networks currently employed rely …