Results 1 to 10 of about 22,057,894 (243)
Frontiers in Psychology, 2019 Exploratory analyses are an important first step in psychological research, particularly in problem-based research where various variables are often included from multiple theoretical perspectives not studied together in combination before.
Nitin Bhushan +5 more
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Probabilistic Graphical Model Representation in Phylogenetics [PDF]
Systematic Biology, 2013 Recent years have seen a rapid expansion of the model space explored in statistical phylogenetics, emphasizing the need for new approaches to statistical model representation and software development.
Boussau, Bastien +5 more
core +4 more sources
Bolt-Loosening Monitoring Framework Using an Image-Based Deep Learning and Graphical Model. [PDF]
Sensors (Basel), 2020 In this study, we investigate a novel idea of using synthetic images of bolts which are generated from a graphical model to train a deep learning model for loosened bolt detection.
Pham HC +5 more
europepmc +2 more sources
, 2016 Structured high-cardinality data arises in many domains, and poses a major challenge for both modeling and inference. Graphical models are a popular approach to modeling structured data but they are unsuitable for high-cardinality variables.
Bui, Hung +5 more
core +3 more sources
Discussion: Latent variable graphical model selection via convex optimization [PDF]
arXiv.org, 2012 Discussion of "Latent variable graphical model selection via convex optimization" by Venkat Chandrasekaran, Pablo A. Parrilo and Alan S. Willsky [arXiv:1008.1290].Comment: Published in at http://dx.doi.org/10.1214/12-AOS984 the Annals of Statistics ...
Giraud, Christophe, Tsybakov, Alexandre
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A Tighter Bound for Graphical Models [PDF]
Neural Computation, 2001 We present a method to bound the partition function of a Boltzmann machine neural network with any odd-order polynomial. This is a direct extension of the mean-field bound, which is first order. We show that the third-order bound is strictly better than mean field.
M.A.R. Leisink, Hilbert J. Kappen
openalex +7 more sources
Statistical Science, 2004 Statistical applications in fields such as bioinformatics, information retrieval, speech processing, image processing and communications often involve large-scale models in which thousands or millions of random variables are linked in complex ways. Graphical models provide a general methodology for approaching these problems, and indeed many of the ...
Michael I. Jordan
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Equivalence model: A new graphical model for causal inference [PDF]
Epidemiology and Health, 2020 Although several causal models relevant to epidemiology have been proposed, a key question that has remained unanswered is why some people at high-risk for a particular disease do not develop the disease while some people at low-risk do develop it.
Jalal Poorolajal
doaj +2 more sources
A probabilistic graphical model foundation for enabling predictive digital twins at scale [PDF]
Nature Computational Science, 2020 A unifying mathematical formulation is needed to move from one-off digital twins built through custom implementations to robust digital twin implementations at scale.
Michael G. Kapteyn +2 more
semanticscholar +1 more source
Fast and Privacy-Preserving Federated Joint Estimator of Multi-sUGMs
IEEE Access, 2021 Learning multiple related graphs from many distributed and privacy-required resources is an important and common task in neuroscience applications. Medical researchers can comprehensively investigate the diagnostic evidence and understand the cause of ...
Xiao Tan, Tianyi Ma, Tongtong Su
doaj +1 more source