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Grouped Spherical Data Modeling Through Hierarchical Nonparametric Bayesian Models and Its Application to fMRI Data Analysis
期刊论文
IEEE Transactions on Neural Networks and Learning Systems,2024, 卷号: 35, 期号: 4, 页码: 5566-5576
作者:
Fan, Wentao
;
Yang, Lin
;
Bouguila, Nizar
收藏
  |  
浏览/下载:19/0
  |  
提交时间:2024/05/07
Functional magnetic resonance imaging (fMRI) data analysis
hierarchical nonparametric Bayesian model
hierarchical Pitman-Yor (HPY) process
spherical data
variational Bayes (VB)
von Mises-Fisher (VMF)
Unsupervised Grouped Axial Data Modeling via Hierarchical Bayesian Nonparametric Models with Watson Distributions
期刊论文
IEEE Transactions on Pattern Analysis and Machine Intelligence,2022, 卷号: 44, 期号: 12, 页码: 9654-9668
作者:
Fan, Wentao
;
Yang, Lin
;
Bouguila, Nizar
收藏
  |  
浏览/下载:9/0
  |  
提交时间:2025/07/15
Axial data
depth image
gene clustering
hierarchical Dirichlet process
hierarchical nonparametric Bayesian model
hierarchical Pitman-Yor process
variational Bayes
Watson distribution
Fast multivariate empirical cumulative distribution function with connection to kernel density estimation
期刊论文
Computational Statistics and Data Analysis,2021, 卷号: 162
作者:
Langrené, Nicolas
;
Warin, Xavier
收藏
  |  
浏览/下载:18/0
  |  
提交时间:2022/08/29
Empirical distribution function
Fast CDF
Fast KDE
Fast kernel summation
Nonparametric copula estimation
Survival function
Modeling and Clustering Positive Vectors via Nonparametric Mixture Models of Liouville Distributions
期刊论文
IEEE Transactions on Neural Networks and Learning Systems,2020, 卷号: 31, 期号: 9, 页码: 3193-3203
作者:
Fan, Wentao
;
Bouguila, Nizar
收藏
  |  
浏览/下载:8/0
  |  
提交时间:2025/07/15
Averaged collapsed variational Bayes (ACVB)
clustering
Dirichlet process
inverted Beta-Liouville (IBL) distribution
mixture models
nonparametric Bayesian
positive vectors
Spherical data clustering and feature selection through nonparametric Bayesian mixture models with von Mises distributions
期刊论文
Engineering Applications of Artificial Intelligence,2020, 卷号: 94
作者:
Fan, Wentao
;
Bouguila, Nizar
收藏
  |  
浏览/下载:9/0
  |  
提交时间:2025/07/15
Clustering
Feature selection
Mixture models
Nonparametric Bayesian model
Pitman–Yor process
Topic novelty detection
von Mises
The variable precision method for elicitation of probability weighting functions
期刊论文
Decision Support Systems,2020, 卷号: 128
作者:
Chai, Junyi
;
Ngai, Wai Ting Eric
收藏
  |  
浏览/下载:27/0
  |  
提交时间:2021/04/23
Behavioral decision making
Nonparametric elicitation
Probability weighting
Prospect theory
Tradeoff method
Nonparametric Time-Varying Coefficient Models for Panel Data
期刊论文
Statistics in Biosciences,2019, 卷号: 11, 期号: 3, 页码: 548-566
作者:
Lin, Huazhen
;
Hong, Hyokyoung G.
;
Yang, Baoying
;
Liu, Wei
;
Zhang, Yong
收藏
  |  
浏览/下载:14/0
  |  
提交时间:2025/03/14
Collection rate of public pension contributions
Nonparametric time-varying coefficients model
Panel data
Penalized least squares estimation
Axially Symmetric Data Clustering Through Dirichlet Process Mixture Models of Watson Distributions
期刊论文
IEEE Transactions on Neural Networks and Learning Systems,2019, 卷号: 30, 期号: 6, 页码: 1683-1694
作者:
Fan, Wentao
;
Bouguila, Nizar
;
Du, Jixiang
;
Liu, Xin
收藏
  |  
浏览/下载:5/0
  |  
提交时间:2025/07/15
Axially symmetric
clustering
Dirichlet process
gene expression
mixture models
nonparametric Bayesian
variational inference
Nonparametric Hierarchical Bayesian Models for Positive Data Clustering Based on Inverted Dirichlet-Based Distributions
期刊论文
IEEE Access,2019, 卷号: 7, 页码: 83600-83614
作者:
Fan, Wentao
;
Bouguila, Nizar
收藏
  |  
浏览/下载:9/0
  |  
提交时间:2025/07/15
Clustering
Inverted Dirichlet
Mixture models
Nonparametric Bayesian model
Stochastic variational inference
Online Learning of Hierarchical Pitman-Yor Process Mixture of Generalized Dirichlet Distributions with Feature Selection
期刊论文
IEEE Transactions on Neural Networks and Learning Systems,2017, 卷号: 28, 期号: 9, 页码: 2048-2061
作者:
Fan, Wentao
;
Sallay, Hassen
;
Bouguila, Nizar
收藏
  |  
浏览/下载:6/0
  |  
提交时间:2025/07/16
Generalized Dirichlet (GD)
hierarchical Pitman-Yor process
mixture models
nonparametric Bayesian
scene recognition
variational inference
video segmentation