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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
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 …
[HTML][HTML] Machine learning for anomaly detection in particle physics
The detection of out-of-distribution data points is a common task in particle physics. It is used
for monitoring complex particle detectors or for identifying rare and unexpected events that …
for monitoring complex particle detectors or for identifying rare and unexpected events that …
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 …
Quantum anomaly detection in the latent space of proton collision events at the LHC
The ongoing quest to discover new phenomena at the LHC necessitates the continuous
development of algorithms and technologies. Established approaches like machine …
development of algorithms and technologies. Established approaches like machine …
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 …
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 …
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 …
Application of quantum machine learning using quantum kernel algorithms on multiclass neuron M-type classification
The functional characterization of different neuronal types has been a longstanding and
crucial challenge. With the advent of physical quantum computers, it has become possible to …
crucial challenge. With the advent of physical quantum computers, it has become possible to …