Results 21 to 30 of about 31,307,485 (221)
The Semi-Hierarchical Dirichlet Process and Its Application to Clustering Homogeneous Distributions [PDF]
, 2020 Assessing homogeneity of distributions is an old problem that has received considerable attention, especially in the nonparametric Bayesian literature.
Mario Beraha, A. Guglielmi, F. Quintana
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Dirichlet Process Prior for Student’s t Graph Variational Autoencoders
Future Internet, 2021 Graph variational auto-encoder (GVAE) is a model that combines neural networks and Bayes methods, capable of deeper exploring the influential latent features of graph reconstruction.
Yuexuan Zhao, Jing Huang
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Dirichlet mixtures, the Dirichlet process, and the structure of protein space. [PDF]
J Comput Biol, 2013 Abstract The Dirichlet process is used to model probability distributions that are mixtures of an unknown number of components. Amino acid frequencies at homologous positions within related proteins have been fruitfully modeled by Dirichlet mixtures, and we use the Dirichlet process to derive such mixtures with an unbounded number of ...
Nguyen VA, Boyd-Graber J, Altschul SF.
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Dirichlet depths for point process [PDF]
Electronic Journal of Statistics, 2021 Statistical depths have been well studied for multivariate and functional data over the past few decades, but remain under-explored for point processes. A first attempt on the notion of point process depth was conducted recently where the depth was defined as a weighted product of two terms: (1) the probability of the number of events in each process ...
Qi, Kai, Chen, Yang, Wu, Wei
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Multilinear Dirichlet Processes
CoRR, 2021 Dependent Dirichlet processes (DDP) have been widely applied to model data from distributions over collections of measures which are correlated in some way. On the other hand, in recent years, increasing research efforts in machine learning and data mining have been dedicated to dealing with data involving interactions from two or more factors. However,
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Mathematics, 2022 In this research, we investigate an optimal control problem governed by elliptic PDEs with Dirichlet boundary conditions on complex connected domains, which can be utilized to model the cooling process of concrete dam pouring.
Mengya Su, Liuqing Xie, Zhiyue Zhang
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Rank-Based Mixture Models for Temporal Point Processes
Frontiers in Applied Mathematics and Statistics, 2022 Temporal point process, an important area in stochastic process, has been extensively studied in both theory and applications. The classical theory on point process focuses on time-based framework, where a conditional intensity function at each given ...
Yang Chen, Yijia Ma, Wei Wu
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Approximation of Space-Time Fractional Equations
Fractal and Fractional, 2021 The aim of this paper is to provide approximation results for space-time non-local equations with general non-local (and fractional) operators in space and time.
Raffaela Capitanelli, Mirko D’Ovidio
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Background Subtraction with Dirichlet Processes [PDF]
, 2012 Background subtraction is an important first step for video analysis, where it is used to discover the objects of interest for further processing. Such an algorithm often consists of a background model and a regularisation scheme. The background model determines a per-pixel measure of if a pixel belongs to the background or the foreground, whilst the ...
Tom S. F. Haines, Tao Xiang 0002
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Generative Supervised Classification Using Dirichlet Process Priors. [PDF]
, 2010 Choosing the appropriate parameter prior distributions associated to a given Bayesian model is a challenging problem. Conjugate priors can be selected for simplicity motivations.
Davy, Manuel +3 more
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