Results 31 to 40 of about 297,382 (270)
Characterizing the Conditional Galaxy Property Distribution Using Gaussian Mixture Models
The Astrophysical Journal, 2023 Line-intensity mapping (LIM) is a promising technique to constrain the global distribution of galaxy properties. To combine LIM experiments probing different tracers with traditional galaxy surveys and fully exploit the scientific potential of these ...
Yucheng Zhang +7 more
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Variational learning for Gaussian mixture models [PDF]
IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 2006 This paper proposes a joint maximum likelihood and Bayesian methodology for estimating Gaussian mixture models. In Bayesian inference, the distributions of parameters are modeled, characterized by hyperparameters. In the case of Gaussian mixtures, the distributions of parameters are considered as Gaussian for the mean, Wishart for the covariance, and ...
Nikolaos, Nasios, Adrian G, Bors
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Uniform convergence rates and uniform adaptive estimation in mixtures of regressions [PDF]
, 2018 In this thesis, we develop theoretical tools to examine estimators in non-parametric regression models in regard of uniform convergence rates and uniform adaptivity with respect to the smoothness of the parameter functions.
Werner, Heiko
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The whole and its parts: Visualizing Gaussian mixture models
Visual InformaticsGaussian mixture models are classical but still popular machine learning models. An appealing feature of Gaussian mixture models is their tractability, that is, they can be learned efficiently and exactly from data, and also support efficient exact ...
Joachim Giesen +4 more
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Scale Mixture of Gaussian Modelling of Polarimetric SAR Data
EURASIP Journal on Advances in Signal Processing, 2010 This paper describes a flexible non-Gaussian statistical method used to model polarimetric synthetic aperture radar (POLSAR) data. We outline the theoretical basis of the well-know product model as described by the class of Scale Mixture models and ...
Anthony P. Doulgeris +1 more
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Estimating the Joint Probability of Scenario Parameters With Gaussian Mixture Copula Models
IEEE Open Journal of Intelligent Transportation SystemsThis paper presents the first application of Gaussian Mixture Copula Models to the statistical modeling of driving scenarios for the safety validation of automated driving systems. Knowledge of the joint probability distribution of scenario parameters is
Christian Reichenbacher +3 more
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Towards Robust 3D Face Verification Using Gaussian Mixture Models
International Journal of Advanced Robotic Systems, 2012 This paper focuses on the use of Gaussian Mixture models (GMM) for 3D face verification. A special interest is taken in practical aspects of 3D face verification systems, where all steps of the verification procedure need to be automated and no meta-data,
Janez Križaj +2 more
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Geosciences, 2018 We discuss the influence of different statistical models in the prediction of porosity and litho-fluid facies from logged and inverted acoustic impedance (Ip) values.
Mattia Aleardi
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Antenna Classification Using Gaussian Mixture Models (GMM) and Machine Learning
IEEE Open Journal of Antennas and Propagation, 2020 Radio frequency fingerprinting (RFF) is the concept arising from classification of wireless emitters due to their unique radio frequency features. RFF has been further extended to applications including both RF devices classification and wireless signal ...
Yihan Ma, Yang Hao
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Adaptive Seeding for Gaussian Mixture Models
, 2017 We present new initialization methods for the expectation-maximization algorithm for multivariate Gaussian mixture models. Our methods are adaptions of the well-known $K$-means++ initialization and the Gonzalez algorithm.
AP Dempster +13 more
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