QUANTUMOONLIGHT: A low-code platform to experiment with quantum machine learning

Article Computer Science, Information Systems

Experimental Evaluation of Quantum Machine Learning Algorithms

Ricardo Daniel Monteiro Simoes et al.

Summary: Machine learning and quantum computing have made considerable progress, and their combination holds great promise. There have been theoretical contributions and experiments on quantum simulators for quantum machine learning algorithms. However, many questions regarding the potential of machine learning on quantum computers remain unanswered.

IEEE ACCESS (2023)

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Review Physics, Multidisciplinary

Quantum Machine Learning: A Review and Case Studies

Amine Zeguendry et al.

Summary: Despite the success of classical machine learning, it remains resource-intensive. With the increasing trend towards high-speed computing, the advantages of quantum computing in machine learning are being explored. This study aims to review the current state of Quantum Machine Learning from a conventional techniques perspective.

ENTROPY (2023)

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Article Computer Science, Artificial Intelligence

Comparative performance analysis of quantum machine learning with deep learning for diabetes prediction

Himanshu Gupta et al.

Summary: The study aimed to develop prediction models using deep learning and quantum machine learning techniques to reduce the lethality associated with diabetes. The results showed that the deep learning model outperformed the quantum machine learning model in terms of diabetes prediction accuracy.

COMPLEX & INTELLIGENT SYSTEMS (2022)

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Article Computer Science, Software Engineering

Static test flakiness prediction: How Far Can We Go?

Valeria Pontillo et al.

Summary: Test flakiness refers to the occurrence of a test case exhibiting both passing and failing behavior when run against the same code. This study investigates and predicts test flakiness using machine learning techniques and static metrics. The research also highlights the impact of production code characteristics on the performance of flaky test prediction models.

EMPIRICAL SOFTWARE ENGINEERING (2022)

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Article Computer Science, Theory & Methods

Quantum Algorithm Implementations for Beginners

J. Abhijith et al.

Summary: As quantum computers become more accessible, there is a growing need to train quantum programmers. This review introduces the principles of quantum programming and provides guidance on implementing quantum algorithms on real quantum hardware. It serves as a blueprint for computer scientists, physicists, and engineers interested in quantum algorithms.

ACM TRANSACTIONS ON QUANTUM COMPUTING (2022)

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Review Computer Science, Software Engineering