Results 71 to 80 of about 557,766 (311)
Structure analysis of growing network based on partial differential equations
Journal of Hebei University of Science and Technology, 2016 The topological structure is one of the most important contents in the complex network research. Therein the node degree and the degree distribution are the most basic characteristic quantities to describe topological structure. In order to calculate the
Junbo JIA, Zhen JIN
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Entropy, 2021 The Variational AutoEncoder (VAE) has made significant progress in text generation, but it focused on short text (always a sentence). Long texts consist of multiple sentences.
Kun Zhao +3 more
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, 2009 In the field of quality of health care measurement, one approach to assessing patient sickness at admission involves a logistic regression of mortality within 30 days of admission on a fairly large number of sickness indicators (on the order of 100) to ...
Draper, D., Fouskakis, D., Ntzoufras, I.
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Mixed-mode oscillations and interspike interval statistics in the stochastic FitzHugh-Nagumo model [PDF]
, 2012 We study the stochastic FitzHugh-Nagumo equations, modelling the dynamics of neuronal action potentials, in parameter regimes characterised by mixed-mode oscillations.
Birkhoff G +11 more
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TEMMUS: A Mobility Predictor based on Temporal Markov Model with User Similarity
Brazilian Symposium on Computer Networks and Distributed Systems, 2019 Location-Based Social Networks (LBSN) data contains spatial, temporal, and social features of user activity, providing valuable information that is currently available on large-scale and low-cost fashion via traditional data collection methods.
Felipe Araújo +4 more
semanticscholar +1 more source
Advanced Science, EarlyView.scPER presents an adversarial‐autoencoder framework that deconvolves bulk total RNA‐seq to quantify tumor‐microenvironment cell types and uncover phenotype‐linked subclusters. Across diverse benchmarks, scPER improves accuracy over existing tools.
Bingrui Li, Xiaobo Zhou, Raghu Kalluri
wiley +1 more source
Multivariate Wishart Stochastic Volatility Models [PDF]
, 2010 We generalize the basic Wishart multivariate stochastic volatility model of Philipov and Glickmann (2006) to encompass regime switching behavior. The latent state variable is driven by a first-order Markov process. In order to estimate the proposed model
Gribisch, Bastian, Liesenfeld, Roman
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Clustering South African households based on their asset status using latent variable models [PDF]
, 2014 The Agincourt Health and Demographic Surveillance System has since 2001 conducted a biannual household asset survey in order to quantify household socio-economic status (SES) in a rural population living in northeast South Africa.
Clark, Samuel J. +5 more
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Mechanism‐Driven Screening of Membrane‐Targeting and Pore‐Forming Antimicrobial Peptides
Advanced Science, EarlyView.To combat antibiotic resistance, this study employs mechanism‐driven screening with machine learning to identify pore‐forming antimicrobial peptides from amphibian and human metaproteomes. Seven peptides are validated, showing minimal toxicity and membrane disruption.
Jiaxuan Li +9 more
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Modeling the exchange rate using price levels and country risk
Cogent Economics & Finance, 2015 This paper builds two factor discrete time models in order to investigate the effect of sovereign risk on the nominal exchange rates in a Markov switching framework. The empirical section of the paper uses seven currencies from Chile, the Czech Republic,
Gábor Regős
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