204,674 results for machine learning
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Journal Article
The rise of scientific machine learning: a perspective on combining mechanistic modelling with machine learning for systems biology
Both machine learning and mechanistic modelling approaches have been used independently with great success in systems biology. Machine learning excels in deriving statistical relationships and quantitative prediction from data, while mechanistic modelling is a powerful approach to capture knowledge…
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Journal Article Full text
Machine Learning-Supported Designing of Human–Machine Interfaces
The design and functionality of the human–machine interface (HMI) significantly affects operational efficiency and safety related to process control. Alarm management techniques consider the cognitive model of operators, but mainly only from a signal perception point of view. To develop a…
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Journal Article
Enhancing DGA Detection with Machine Learning Algorithms
…type. For character-based DGA detection, we employed seven traditional machine learning methods: support vector machine, extremely randomized trees, logistic regression, Gaussian naive Bayes, nearest centroid, random forests, and k-nearest neighbors. We applied a featureful approach, using features…
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Journal Article
Probabilistic machine learning for breast cancer classification
…the results reproducible, also in accordance with the latest trending in machine learning research, named Papers with Code. The various steps taken for the code development are introduced in detail but also the results are visually displayed and critically analyzed also in the sense of explainable…
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Residual matrix product state for machine learning
Tensor network, which originates from quantum physics, is emerging as an efficient tool for classical and quantum machine learning. Nevertheless, there still exists a considerable accuracy gap between tensor network and the sophisticated neural network models for classical machine learning. In this…
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Journal Article
Machine Learning in Psychometrics and Psychological Research
…complementing the analytical workflow of psychological experiments with Machine Learning-based analysis will both maximize accuracy and minimize replicability issues. As compared to statistical inference, ML analysis of experimental data is model agnostic and primarily focused on prediction rather…
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Journal Article
Machine learning glass transition temperature of polymers
As an important thermophysical property, polymers' glass transition temperature, Tg, could sometimes be difficult to determine experimentally. Modeling methods, particularly data-driven approaches, are promising alternatives to predictions of Tg in a fast and robust way. The molecular traceless…
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Journal Article
Machine learning prediction of academic collaboration networks
…examined both network and non-network attributes. Using four machine learning predictive algorithms (LASSO, Neural Network, Gradient Boosting, and Random Forest) our results show that, over various model specifications: (i) best model link formation accuracy is larger than 80%, (ii) among the…
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Journal Article
Pediatric Severe Sepsis Prediction Using Machine Learning
…methods are needed to facilitate this early detection.Objective: Can a machine-learning based prediction algorithm using electronic healthcare record (EHR) data predict severe sepsis onset in pediatric populations?Methods: EHR data were collected from a retrospective set of de-identified pediatric…
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Journal Article
The Machine Learning landscape of top taggers
Based on the established task of identifying boosted, hadronically decaying top quarks, we compare a wide range of modern machine learning approaches. Unlike most established methods they rely on low-level input, for instance calorimeter output. While their network architectures are vastly…
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Journal Article
Artificial Intelligence, Machine Learning, and Cardiovascular Disease
…recently, with the advent of advances in computing, algorithms enabling machine learning, especially deep learning networks that mimic the human brain in function, there has been renewed interest to use them in clinical medicine. In cardiovascular medicine, AI-based systems have found new…
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Journal Article
Machine learning uncertainties with adversarial neural networks
Abstract Machine Learning is a powerful tool to reveal and exploit correlations in a multi-dimensional parameter space. Making predictions from such correlations is a highly non-trivial task, in particular when the details of the underlying dynamics of a theoretical model are not fully understood…
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Journal Article
Machine Learning of Noise-Resilient Quantum Circuits
Noise mitigation and reduction will be crucial for obtaining useful answers from near-term quantum computers. In this work, we present a general framework based on machine learning for reducing the impact of quantum hardware noise on quantum circuits. Our method, called noise-aware circuit learning…
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Journal Article
Machine Learning for Long-Distance Quantum Communication
Machine learning can help us in solving problems in the context of big-data analysis and classification, as well as in playing complex games such as Go. But can it also be used to find novel protocols and algorithms for applications such as large-scale quantum communication? Here we show that…
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Journal Article Full text
Money Neutrality, Monetary Aggregates and Machine Learning
…methodology we employ is support vector machines (SVM) from the area of machine learning. The empirical results show that: (a) The Divisia monetary aggregates outperform the simple sum ones and (b) both monetary aggregates can directionally forecast the Eurocoin index reaching the highest accuracy…
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Journal Article Full text
Automating XML Markup using Machine Learning Techniques
…the Self-Organising Map (SOM) algorithm in conjunction with an inductive learning algorithm, C5.0. The SOM algorithm clusters the XML marked-up documents on a two-dimensional map such that documents having similar content are placed close to each other. The C5.0 algorithm learns and applies markup…
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Journal Article
Quantum machine learning assisted lung cancer telemedicine
…of the loss function and maximum correlation of data from the quantum machine learning model, and high teleportation fidelity (96% transmission fidelity for biosignals and 98% teleportation fidelity for doses LITT). This shows the proposed telemedicine schemes anticipated solutions for the…
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Journal Article
Machine learning techniques to select variable stars
In order to perform a supervised classification of variable stars, we propose and evaluate a set of six features extracted from the magnitude density of the light curves. They are used to train automatic classification systems using state-of-the-art classifiers implemented in the R statistical…
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Journal Article
Machine Learning in Modeling of Mouse Behavior
Mouse behavior is a primary outcome in evaluations of therapeutic efficacy. Exhaustive, continuous, multiparametric behavioral phenotyping is a valuable tool for understanding the pathophysiological status of mouse brain diseases. Automated home cage behavior analysis produces highly granulated…
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Journal Article
Machine Learning and technoecological conditions of sensing
In what way can machine learning be understood as a computational mode of sensing? How does the practice of making sense take place in the context of developing machine learning applications? What assumptions and conflicts are constitutive for that very process of sensing? Bringing case studies…
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