Results 91 to 100 of about 2,977,466 (210)

Quantum-classical convolutional neural networks in radiological image classification

, 2023
5666Quantum machine learning is receiving significant attention currently, but its usefulness in comparison to classical machine learning techniques for practical applications remains unclear.
Lorenz, Jeanette Miriam, Messerer, Thomas, Matic, Andrea, Monnet, Maureen, Schachtner, Balthasar   +4 more
core   +1 more source

Benchmarking MedMNIST dataset on real quantum hardware

Scientific Reports
Quantum machine learning (QML) has emerged as a promising domain to leverage the computational capabilities of quantum systems to solve complex classification tasks.
Gurinder Singh, Hongni Jin, Kenneth M. Merz Jr.   +2 more
doaj   +1 more source

A hybrid QSVM-QNN approach for breast cancer diagnosis using quantum feature maps [PDF]

PeerJ Computer Science
Quantum assisted machine learning (QML) have the potential to outperform the classical Machine Learning models by utilizing the quantum feature maps embeddings and variational circuits.
Vikesh Yadav, Savita Kumari Sheoran, Rakesh Kumar Sheoran   +2 more
doaj   +2 more sources

Certification of quantum non-Guassian photon coincidences through lossy channels

Quantum non-Gaussianity is a stricter criterion and the next step after non-classicality in the classification of quantum states. We will present our experimental results on the certification of quantum non-Gaussian coincidences through a noisy channel.
Lee, Jaewon,, Höfling, Sven, Littmann, Jan-Heinrich,, Checchinato, Riccardo,, Predojević, Ana,, Schneider, Christian, Filip, Radim, Lachman, Lukáš   +7 more
core   +1 more source

A quantum-implementable neural network model

, 2017
A quantum-implementable neural network, namely quantum probability neural network (QPNN) model, is proposed in this paper. QPNN can use quantum parallelism to trace all possible network states to improve the result. Due to its unique quantum nature, this
Charbon, Edoardo, Chen, Jialin, Wang, Lingli, Jialin Chen, Edoardo Charbon, Lingli Wang   +5 more
core   +1 more source

Quantum neural networks facilitating quantum state classification

CoRR
The classification of quantum states into distinct classes poses a significant challenge. In this study, we address this problem using quantum neural networks in combination with a problem-inspired circuit and customised as well as predefined ansätz. To facilitate the resource-efficient quantum state classification, we construct the dataset of quantum ...
Diksha Sharma, Vivek Balasaheb Sabale, Thirumalai M., Atul Kumar   +3 more
openaire   +3 more sources

Epistemic vs Ontic Classification of Quantum Entangled States?

, 2015
In this brief paper, starting from recent works, we analyze from a conceptual point of view this basic question: can the nature of quantum entangled states be interpreted ontologically or epistemologically? According to some works, the degrees of freedom
Caponigro, Michele, Giannetto, Enrico
core  

Epistemic vs Ontic Classification of quantum entangled states? [PDF]

, 2012
In this brief paper, starting from recent works, we analyze from conceptual point of view this basic question: can be the nature of quantum entangled states interpreted ontologically or epistemologically? According some works, the degrees of freedom (and
Caponigro, Michele, Gianneto, Enrico, Giannetto, Enrico   +2 more
core   +1 more source

Scalable parameterized quantum circuits classifier

Scientific Reports
As a generalized quantum machine learning model, parameterized quantum circuits (PQC) have been found to perform poorly in terms of classification accuracy and model scalability for multi-category classification tasks. To address this issue, we propose a
Xiaodong Ding, Zhihui Song, Jinchen Xu, Yifan Hou, Tian Yang, Zheng Shan   +5 more
doaj   +1 more source

Quantum Machine Learning for Malware Classification

In a context of malicious software detection, machine learning (ML) is widely used to generalize to new malware. However, it has been demonstrated that ML models can be fooled or may have generalization problems on malware that has never been seen. We investigate the possible benefits of quantum algorithms for classification tasks.
Grégoire Barrué, Tony Quertier
openaire   +3 more sources