Results 21 to 30 of about 1,244,068 (326)
Journal of Machine Learning Research, 2014 Stable random variables are motivated by the central limit theorem for densities with (potentially) unbounded variance and can be thought of as natural generalizations of the Gaussian distribution to skewed and heavy-tailed phenomenon. In this paper, we introduce stable graphical (SG) models, a class of multivariate stable densities that can also be ...
Misra N, Kuruoglu E E
openaire +5 more sources
Graphic Models of Nicknames in the German-Speaking Internet-Space
Vestnik Volgogradskogo Gosudarstvennogo Universiteta. Seriâ 2. Âzykoznanie, 2015 The object of the study is a specific anthroponymic element of the onomastic system in German – the network name (nickname) and its representation in the German section of the Internet.
Viktoriya Viktorovna Kazyaba
doaj +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Interpretation of 3-D scene through LiDAR point clouds has been a hot research topic for decades. To utilize measured points in the scene, assigning unique tags to the points of the scene with labels linking to individual objects plays a crucial role in ...
Yusheng Xu +6 more
doaj +1 more source
Inferring Differential Networks by Integrating Gene Expression Data With Additional Knowledge
Frontiers in Genetics, 2021 Evidences increasingly indicate the involvement of gene network rewiring in disease development and cell differentiation. With the accumulation of high-throughput gene expression data, it is now possible to infer the changes of gene networks between two ...
Chen Liu +3 more
doaj +1 more source
Cavity approximation for graphical models [PDF]
Physical Review E, 2007 Extension to factor graphs and comments on related work ...
Rizzo, T. +3 more
openaire +5 more sources
, 2020 Paired comparison data considered in this paper originate from the comparison of a large number N of individuals in couples. The dataset is a collection of results of contests between two individuals when each of them has faced n opponents, where n is ...
Corff, Sylvain Le +2 more
core +2 more sources
Projective Latent Dependency Forest Models
IEEE Access, 2019 Latent dependence forest models (LDFM) are a new type of probabilistic models with the advantage of not requiring the difficult procedure of structure learning in model learning.
Yong Jiang, Yang Zhou, Kewei Tu
doaj +1 more source
Tests for Gaussian graphical models [PDF]
Computational Statistics & Data Analysis, 2009 Gaussian graphical models are promising tools for analysing genetic networks. In many applications, biologists have some knowledge of the genetic network and may want to assess the quality of their model using gene expression data. This is why one introduces a novel procedure for testing the neighborhoods of a Gaussian graphical model.
Verzelen, Nicolas, Villers, Fanny
openaire +5 more sources
Frontiers in Genetics, 2019 High-throughput microbial sequencing techniques, such as targeted amplicon-based and metagenomic profiling, provide low-cost genomic survey data of microbial communities in their natural environment, ranging from marine ecosystems to host-associated ...
Grace Yoon +2 more
doaj +1 more source
Sparse Cholesky Covariance Parametrization for Recovering Latent Structure in Ordered Data
IEEE Access, 2020 The sparse Cholesky parametrization of the inverse covariance matrix is directly related to Gaussian Bayesian networks. Its counterpart, the covariance Cholesky factorization model, has a natural interpretation as a hidden variable model for ordered ...
Irene Cordoba +3 more
doaj +1 more source