Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Machine learning for alloys
Alloy modelling has a history of machine-learning-like approaches, preceding the tide of
data-science-inspired work. The dawn of computational databases has made the integration …
data-science-inspired work. The dawn of computational databases has made the integration …
Learning quantum systems
The future development of quantum technologies relies on creating and manipulating
quantum systems of increasing complexity, with key applications in computation, simulation …
quantum systems of increasing complexity, with key applications in computation, simulation …
Generalization in quantum machine learning from few training data
Modern quantum machine learning (QML) methods involve variationally optimizing a
parameterized quantum circuit on a training data set, and subsequently making predictions …
parameterized quantum circuit on a training data set, and subsequently making predictions …
Provably efficient machine learning for quantum many-body problems
Classical machine learning (ML) provides a potentially powerful approach to solving
challenging quantum many-body problems in physics and chemistry. However, the …
challenging quantum many-body problems in physics and chemistry. However, the …
Phase transitions in particle physics: Results and perspectives from lattice quantum chromo-dynamics
Phase transitions in a non-perturbative regime can be studied by ab initio Lattice Field
Theory methods. The status and future research directions for LFT investigations of Quantum …
Theory methods. The status and future research directions for LFT investigations of Quantum …
A systematic review on supervised and unsupervised machine learning algorithms for data science
Abstract Machine learning is as growing as fast as concepts such as Big data and the field of
data science in general. The purpose of the systematic review was to analyze scholarly …
data science in general. The purpose of the systematic review was to analyze scholarly …
Artificial intelligence and machine learning for quantum technologies
In recent years the dramatic progress in machine learning has begun to impact many areas
of science and technology significantly. In the present perspective article, we explore how …
of science and technology significantly. In the present perspective article, we explore how …
Machine learning and the physical sciences
Machine learning (ML) encompasses a broad range of algorithms and modeling tools used
for a vast array of data processing tasks, which has entered most scientific disciplines in …
for a vast array of data processing tasks, which has entered most scientific disciplines in …
From DFT to machine learning: recent approaches to materials science–a review
Recent advances in experimental and computational methods are increasing the quantity
and complexity of generated data. This massive amount of raw data needs to be stored and …
and complexity of generated data. This massive amount of raw data needs to be stored and …
Quantum convolutional neural networks
Neural network-based machine learning has recently proven successful for many complex
applications ranging from image recognition to precision medicine. However, its direct …
applications ranging from image recognition to precision medicine. However, its direct …