AIMC Topic: Normal Distribution

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A New Approach for Including Social Conventions into Social Robots Navigation by Using Polygonal Triangulation and Group Asymmetric Gaussian Functions.

Sensors (Basel, Switzerland) Jun 18, 2022
Many authors have been working on approaches that can be applied to social robots to allow a more realistic/comfortable relationship between humans and robots in the same space. This paper proposes a new navigation strategy for social environments by...
Social Interaction Computer Simulation Normal Distribution Robotics Algorithms Humans
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An Animation Model Generation Method Based on Gaussian Mutation Genetic Algorithm to Optimize Neural Network.

Computational intelligence and neuroscience Jun 3, 2022
With the rapid development of computer graphics, 3D animation has been applied to all fields of people's lives, especially in the industries of film and television works, games, and entertainment. The wide application of animation technology makes it...
Mutation Motion Pictures Neural Networks, Computer Humans Computer Graphics Normal Distribution Algorithms
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Approximation properties of Gaussian-binary restricted Boltzmann machines and Gaussian-binary deep belief networks.

Neural networks : the official journal of the International Neural Network Society Jun 2, 2022
Despite the successful use of Gaussian-binary restricted Boltzmann machines (GB-RBMs) and Gaussian-binary deep belief networks (GB-DBNs), little is known about their theoretical approximation capabilities to represent distributions of continuous rand...
Neural Networks, Computer Computer Simulation Normal Distribution Probability
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Representing globally accurate reactive potential energy surfaces with complex topography by combining Gaussian process regression and neural networks.

Physical chemistry chemical physics : PCCP Jun 1, 2022
There has been increasing attention in using machine learning technologies, such as neural networks (NNs) and Gaussian process regression (GPR), to model multi-dimensional potential energy surfaces (PESs). A PES constructed using NNs features high ac...
Neural Networks, Computer Normal Distribution
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AutoML-ID: automated machine learning model for intrusion detection using wireless sensor network.

Scientific reports May 31, 2022
Momentous increase in the popularity of explainable machine learning models coupled with the dramatic increase in the use of synthetic data facilitates us to develop a cost-efficient machine learning model for fast intrusion detection and prevention ...
Linear Models Normal Distribution Bayes Theorem Wireless Technology Computer Simulation Machine Learning
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More Than Words: An Invited Commentary Regarding "Quantitative Patient-Reported Experience Measures Derived From Natural Language Processing Have a Normal Distribution and No Ceiling Effect".

Quality management in health care May 27, 2022
Natural Language Processing Patient Reported Outcome Measures Humans Normal Distribution
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Physics-constrained deep active learning for spatiotemporal modeling of cardiac electrodynamics.

Computers in biology and medicine May 10, 2022
The development of computational modeling and simulation have immensely benefited the study of cardiac disease mechanisms and facilitated the optimal disease diagnosis and treatment design. The dynamic propagation of cardiac electrical signals are of...
Physics Heart Normal Distribution Computer Simulation Machine Learning
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Effective prediction of soil micronutrients using Additive Gaussian process with RAM augmentation.

Computational biology and chemistry Apr 20, 2022
In soil chemistry, the nutrients exhibit non-linear and complex relationships owing to their stochastic nature but mostly their similarity is a function of the distance between the data points. The similarity assessment using distance metrics is a po...
Algorithms Soil Micronutrients Normal Distribution Deep Learning
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Automatic Evaluation of Motor Rehabilitation Exercises Based on Deep Mixture Density Neural Networks.

Journal of biomedical informatics Apr 20, 2022
An automatic assessment system for physical telerehabilitation could reduce the time and cost of treatments. But such assessment involves stochastic uncertainties, nonlinearities, and complexities of human movement. Probabilistic models and deep stru...
Reproducibility of Results Normal Distribution Exercise Therapy Neural Networks, Computer Humans Algorithms
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Data Pre-Processing Using Neural Processes for Modeling Personalized Vital-Sign Time-Series Data.

IEEE journal of biomedical and health informatics Apr 14, 2022
Clinical time-series data retrieved from electronic medical records are widely used to build predictive models of adverse events to support resource management. Such data is often sparse and irregularly-sampled, which makes it challenging to use many...
Models, Theoretical Time Factors Humans Machine Learning Electronic Health Records Normal Distribution
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