Results 51 to 60 of about 154,173 (259)
Quantum Machine Learning Playground
IEEE Computer Graphics and ApplicationsAccepted to IEEE Computer Graphics and Applications.
Pascal Debus +2 more
openaire +3 more sources
Synchrotron Radiation for Quantum Technology
Advanced Functional Materials, EarlyView.Materials and interfaces underpin quantum technologies, with synchrotron and FEL methods key to understanding and optimizing them. Advances span superconducting and semiconducting qubits, 2D materials, and topological systems, where strain, defects, and interfaces govern performance.
Oliver Rader +10 more
wiley +1 more source
Indoor–Outdoor Detection in Mobile Networks Using Quantum Machine Learning Approaches
Computers, 2021 Communication networks are managed more and more by using artificial intelligence. Anomaly detection, network monitoring and user behaviour are areas where machine learning offers advantages over more traditional methods.
Frank Phillipson +2 more
doaj +1 more source
Strategy for quantum algorithm design assisted by machine learning
, 2014 We propose a method for quantum algorithm design assisted by machine learning. The method uses a quantum-classical hybrid simulator, where a "quantum student" is being taught by a "classical teacher." In other words, in our method, the learning system is
Bang, Jeongho +4 more
core +1 more source
Machine learning for quantum matter [PDF]
Advances in Physics: X, 2020 34 pages, 4 figures, 290 references.
openaire +3 more sources
Bimetallic Nanoparticles as Cocatalysts for Photocatalytic Hydrogen Production
Advanced Functional Materials, EarlyView.Recent developments have introduced bimetallic nanoparticles as effective cocatalysts for photocatalytic systems. This review explores the rapidly expanding research on bimetallic cocatalysts for photocatalytic production of hydrogen, emphasizing the creation of carrier‐selective contacts, localized surface plasmon resonance effects, methodologies for ...
Yufen Chen +4 more
wiley +1 more source
Taking advantage of noise in quantum reservoir computing
Scientific Reports, 2023 The biggest challenge that quantum computing and quantum machine learning are currently facing is the presence of noise in quantum devices. As a result, big efforts have been put into correcting or mitigating the induced errors. But, can these two fields
L. Domingo, G. Carlo, F. Borondo
doaj +1 more source
Quantum machine learning for quantum anomaly detection
, 2017 Anomaly detection is used for identifying data that deviate from `normal' data patterns. Its usage on classical data finds diverse applications in many important areas like fraud detection, medical diagnoses, data cleaning and surveillance.
Liu, Nana, Rebentrost, Patrick
core +1 more source
Machine learning and quantum devices [PDF]
SciPost Physics Lecture Notes, 2021 These brief lecture notes cover the basics of neural networks and deep learning as well as their applications in the quantum domain, for physicists without prior knowledge. In the first part, we describe training using backpropagation, image classification, convolutional networks and autoencoders.
openaire +4 more sources
Electroactive Metal–Organic Frameworks for Electrocatalysis
Advanced Functional Materials, EarlyView.Electrocatalysis is crucial in sustainable energy conversion as it enables efficient chemical transformations. The review discusses how metal–organic frameworks can revolutionize this field by offering tailorable structures and active site tunability, enabling efficient and selective electrocatalytic processes.
Irena Senkovska +7 more
wiley +1 more source