An introduction to quantum machine learning
Machine learning algorithms learn a desired input-output relation from examples in order to
interpret new inputs. This is important for tasks such as image and speech recognition or …
interpret new inputs. This is important for tasks such as image and speech recognition or …
The quest for a quantum neural network
With the overwhelming success in the field of quantum information in the last decades, the
'quest'for a Quantum Neural Network (QNN) model began in order to combine quantum …
'quest'for a Quantum Neural Network (QNN) model began in order to combine quantum …
A quantum deep convolutional neural network for image recognition
Deep learning achieves unprecedented success involves many fields, whereas the high
requirement of memory and time efficiency tolerance have been the intractable challenges …
requirement of memory and time efficiency tolerance have been the intractable challenges …
Machine learning algorithms in quantum computing: A survey
Machine Learning (ML) aims at designing models that learn from previous experience,
without being explicitly formulated. Applications of machine learning are inexhaustible …
without being explicitly formulated. Applications of machine learning are inexhaustible …
A survey on quantum machine learning: Current trends, challenges, opportunities, and the road ahead
Quantum Computing (QC) claims to improve the efficiency of solving complex problems,
compared to classical computing. When QC is integrated with Machine Learning (ML), it …
compared to classical computing. When QC is integrated with Machine Learning (ML), it …
Quantum computing: an overview across the system stack
Quantum computers, if fully realized, promise to be a revolutionary technology. As a result,
quantum computing has become one of the hottest areas of research in the last few years …
quantum computing has become one of the hottest areas of research in the last few years …
Quantum perceptron over a field and neural network architecture selection in a quantum computer
In this work, we propose a quantum neural network named quantum perceptron over a field
(QPF). Quantum computers are not yet a reality and the models and algorithms proposed in …
(QPF). Quantum computers are not yet a reality and the models and algorithms proposed in …
Quantum machine learning in prediction of breast cancer
Abstract Machine learning (ML) is the most promising subset of artificial intelligence.
Quantum computing is prevalent for fast problem-solving approaches. The complex …
Quantum computing is prevalent for fast problem-solving approaches. The complex …
Diffusion-inspired quantum noise mitigation in parameterized quantum circuits
Parameterized Quantum Circuits (PQCs) have been acknowledged as a leading strategy to
utilize near-term quantum advantages in multiple problems, including machine learning and …
utilize near-term quantum advantages in multiple problems, including machine learning and …
Conglomeration of deep neural network and quantum learning for object detection: Status quo review
The practice of deep neural framework specific to convolutional neural networks
(ConNeuNets) in domain of object detection is substantial. The existing deep ConNeuNets …
(ConNeuNets) in domain of object detection is substantial. The existing deep ConNeuNets …