Results 1 to 10 of about 412,953 (170)
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
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Axioms, 2022 This paper shows a visual analysis and the dependence relationships of COVID-19 mortality data in 50 states plus Washington, D.C., from January 2020 to 1 September 2022.
Jong-Min Kim
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Mathematics, 2022 Strong exogeneity is an important assumption in the study of causal inference, but it is difficult to identify according to its definition. The twin network method provides a graphical model tool for analyzing the variable relationship, involving the ...
Rui Luo +4 more
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Graphical Models for Extremes [PDF]
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2020 SummaryConditional independence, graphical models and sparsity are key notions for parsimonious statistical models and for understanding the structural relationships in the data. The theory of multivariate and spatial extremes describes the risk of rare events through asymptotically justified limit models such as max-stable and multivariate Pareto ...
Engelke, Sebastian, Hitz, Adrien S.
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Graphical Notation for Document Database Modeling
Открытое образование (Москва), 2021 Goals and objectives. Graphical models have proven to be a reliable, clear and convenient tool for creating sketch models of databases. Most of the existing notations are designed for the relational data model, the dominant data model for the last thirty
M. V. Smirnov, R. S. Tolmasov
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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
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Modeling Categorical Variables by Mutual Information Decomposition
Entropy, 2023 This paper proposed the use of mutual information (MI) decomposition as a novel approach to identifying indispensable variables and their interactions for contingency table analysis.
Jiun-Wei Liou +2 more
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On Sufficient Graphical Models
CoRR, 2023 We introduce a sufficient graphical model by applying the recently developed nonlinear sufficient dimension reduction techniques to the evaluation of conditional independence. The graphical model is nonparametric in nature, as it does not make distributional assumptions such as the Gaussian or copula Gaussian assumptions.
Bing Li, Kyongwon Kim
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Conditional Random Field-Guided Multi-Focus Image Fusion
Journal of Imaging, 2022 Multi-Focus image fusion is of great importance in order to cope with the limited Depth-of-Field of optical lenses. Since input images contain noise, multi-focus image fusion methods that support denoising are important.
Odysseas Bouzos +2 more
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Frontiers in Climate, 2021 South Asian monsoon is a phenomena that plays out during June-September every year, due to the northward shift of the ITCZ which causes heavy rainfall over many countries of South Asia, including India.
Adway Mitra
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