Artificial intelligence: A powerful paradigm for scientific research
Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well
known from computer science is broadly affecting many aspects of various fields including …
known from computer science is broadly affecting many aspects of various fields including …
[HTML][HTML] Systematic literature review: Quantum machine learning and its applications
D Peral-García, J Cruz-Benito… - Computer Science …, 2024 - Elsevier
Quantum physics has changed the way we understand our environment, and one of its
branches, quantum mechanics, has demonstrated accurate and consistent theoretical …
branches, quantum mechanics, has demonstrated accurate and consistent theoretical …
Universal expressiveness of variational quantum classifiers and quantum kernels for support vector machines
Abstract Machine learning is considered to be one of the most promising applications of
quantum computing. Therefore, the search for quantum advantage of the quantum …
quantum computing. Therefore, the search for quantum advantage of the quantum …
Anomaly detection in high-energy physics using a quantum autoencoder
The lack of evidence for new interactions and particles at the Large Hadron Collider (LHC)
has motivated the high-energy physics community to explore model-agnostic data-analysis …
has motivated the high-energy physics community to explore model-agnostic data-analysis …
[HTML][HTML] Applications and techniques for fast machine learning in science
In this community review report, we discuss applications and techniques for fast machine
learning (ML) in science—the concept of integrating powerful ML methods into the real-time …
learning (ML) in science—the concept of integrating powerful ML methods into the real-time …
Quantum machine learning framework for virtual screening in drug discovery: a prospective quantum advantage
Abstract Machine Learning for ligand based virtual screening (LB-VS) is an important in-
silico tool for discovering new drugs in a faster and cost-effective manner, especially for …
silico tool for discovering new drugs in a faster and cost-effective manner, especially for …
Practical advantage of quantum machine learning in ghost imaging
Demonstrating the practical advantage of quantum computation remains a long-standing
challenge whereas quantum machine learning becomes a promising application that can be …
challenge whereas quantum machine learning becomes a promising application that can be …
Quantum machine learning on near-term quantum devices: Current state of supervised and unsupervised techniques for real-world applications
The past decade has witnessed significant advancements in quantum hardware,
encompassing improvements in speed, qubit quantity, and quantum volume—a metric …
encompassing improvements in speed, qubit quantity, and quantum volume—a metric …
Hybrid quantum classical graph neural networks for particle track reconstruction
Abstract The Large Hadron Collider (LHC) at the European Organisation for Nuclear
Research (CERN) will be upgraded to further increase the instantaneous rate of particle …
Research (CERN) will be upgraded to further increase the instantaneous rate of particle …
Quantum Machine Learning for b-jet charge identification
A Gianelle, P Koppenburg, D Lucchesi… - Journal of High Energy …, 2022 - Springer
A bstract Machine Learning algorithms have played an important role in hadronic jet
classification problems. The large variety of models applied to Large Hadron Collider data …
classification problems. The large variety of models applied to Large Hadron Collider data …