Results 21 to 30 of about 8,492,854 (308)
CoRR, 2016 Casting neural networks in generative frameworks is a highly sought-after endeavor these days. Contemporary methods, such as Generative Adversarial Networks, capture some of the generative capabilities, but not all. In particular, they lack the ability of tractable marginalization, and thus are not suitable for many tasks.
Or Sharir +3 more
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Machine Learning based on Probabilistic Models Applied to Medical Data: The Case of Prostate Cancer
Journal of Innovation Information Technology and Application, 2023 The growth in the amount of data in companies puts analysts in difficulties when extracting hidden knowledge from data. Several models have emerged that focus on the notion of distances while ignoring the notion of conditional probability density.
Anaclet Tshikutu Bikengela +4 more
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, 2019 Mixtures of experts models provide a framework in which covariates may be included in mixture models. This is achieved by modelling the parameters of the mixture model as functions of the concomitant covariates. Given their mixture model foundation, mixtures of experts models possess a diverse range of analytic uses, from clustering observations to ...
Gormley, Isobel Claire +1 more
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On a Mixture Autoregressive Model
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2000 Summary We generalize the Gaussian mixture transition distribution (GMTD) model introduced by Le and co-workers to the mixture autoregressive (MAR) model for the modelling of non-linear time series. The models consist of a mixture of K stationary or non-stationary AR components. The advantages of the MAR model over the GMTD model include
Wong, CS, Li, WK
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Mixture models for distance sampling detection functions [PDF]
, 2015 Funding: EPSRC DTGWe present a new class of models for the detection function in distance sampling surveys of wildlife populations, based on finite mixtures of simple parametric key functions such as the half-normal. The models share many of the features
David L. Miller (167484) +9 more
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Dealing with Label Switching in Mixture Models Under Genuine Multimodality [PDF]
, 2008 The fitting of finite mixture models is an ill-defined estimation problem as completely different parameterizations can induce similar mixture distributions.
Leisch, Friedrich, Grün, Bettina
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Lessons Learned From the Training of GANs on Artificial Datasets
IEEE Access, 2020 Generative Adversarial Networks (GANs) have made great progress in synthesizing realistic images in recent years. However, they are often trained on image datasets with either too few samples or too many classes belonging to different data distributions.
Shichang Tang
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Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2012 The aim of this paper is to present and discuss the power of the exact likelihood ratio homogeneity testing procedure of the number of components k in the exponential mixture.
Luboš Střelec, Milan Stehlík
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Geodesic Finite Mixture Models [PDF]
Proceedings of the British Machine Vision Conference 2014, 2014 Peer ...
Simó Serra, Edgar +2 more
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Journal of Statistical Software, 2018 We introduce the R package ContaminatedMixt, conceived to disseminate the use of mixtures of multivariate contaminated normal distributions as a tool for robust clustering and classification under the common assumption of elliptically contoured groups ...
Antonio Punzo +2 more
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