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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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, 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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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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Geodesic Finite Mixture Models [PDF]
Proceedings of the British Machine Vision Conference 2014, 2014 Peer ...
Simó Serra, Edgar +2 more
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Sampling from Dirichlet process mixture models with unknown concentration parameter: mixing issues in large data implementations [PDF]
, 2014 We consider the question of Markov chain Monte Carlo sampling from a general stick-breaking Dirichlet process mixture model, with concentration parameter (Formula presented.).
Silvia Liverani +5 more
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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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Frontiers in Psychology, 2021 How children learn grammar is one of the most fundamental questions in cognitive science. Two theoretical accounts, namely, the Early Abstraction and Usage-Based accounts, propose competing answers to this question.
Seamus Donnelly +6 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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Clustering Matrix Variate Longitudinal Count Data
Analytics, 2023 Matrix variate longitudinal discrete data can arise in transcriptomics studies when the data are collected for N genes at r conditions over t time points, and thus, each observation Yn for n=1,…,N can be written as an r×t matrix.
Sanjeena Subedi
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