Results 61 to 70 of about 146,110 (315)
Applying diffusion-based Markov chain Monte Carlo. [PDF]
PLoS ONE, 2017 We examine the performance of a strategy for Markov chain Monte Carlo (MCMC) developed by simulating a discrete approximation to a stochastic differential equation (SDE). We refer to the approach as diffusion MCMC.
Radu Herbei, Rajib Paul, L Mark Berliner
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Detection of Factors Affecting State Transition Based on Non-Homogeneous Markov Chain Model
IEEE Access, 2021 The dependent and independent variables in traditional linear regression models are continuous numerical variables. When the dependent variable or independent variable is a discrete variable, the traditional linear regression model can no longer be used ...
Shen Xiujuan +3 more
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Information and Control, 1976 We investigate the possibility of synthesizing stable probability distribution generators on the basis of a complete system of deterministic elements and generators of random signals described by nonhomogeneous Markov chains. It is shown that such generators can be obtained by constructing some finite Moore automata with special transition functions ...
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CoRR, 2018 The problem of estimating an unknown discrete distribution from its samples is a fundamental tenet of statistical learning. Over the past decade, it attracted significant research effort and has been solved for a variety of divergence measures. Surprisingly, an equally important problem, estimating an unknown Markov chain from its samples, is still far
Yi Hao +2 more
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PDIA6–SCD1 Axis Rewires Lipid Metabolism to Drive Gastric Cancer Progression
Advanced Science, EarlyView.Protein disulfide isomerase A6 (PDIA6) is identified as an oncogenic driver in gastric cancer. PDIA6 directly binds and stabilizes SCD1 by limiting its ubiquitin–proteasome‐mediated degradation, thereby sustaining monounsaturated fatty acid (MUFA)‐enriched lipid homeostasis and lipid metabolic reprogramming.
Zhen Tian +13 more
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Strong Ergodicity in Nonhomogeneous Markov Systems with Chronological Order
MathematicsIn the present, we study the problem of strong ergodicity in nonhomogeneous Markov systems. In the first basic theorem, we relax the fundamental assumption present in all studies of asymptotic behavior.
P.-C.G. Vassiliou
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Markov chain analysis of regional climates [PDF]
Nonlinear Processes in Geophysics, 2010 We present a novel method for regional climate classification that is based on coarse-grained categorical representations of multivariate climate anomalies and a subsequent Markov chain analysis.
S. Mieruch +4 more
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Advanced Science, EarlyView.We introduce a vision‐based real‐time monitoring system for additive manufacturing that detects subtle moisture‐induced degradation via a diffusion model‐based framework. The approach enables nondestructive assessment of moisture‐induced damage level and mechanical performance and establishes a practical route toward more intelligent, reliable, and ...
Jiyoung Jung +4 more
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Stochastic Methods for Analysis of Complex Hardware-Software Systems
Труды Института системного программирования РАН, 2018 In this paper we consider Markov analysis of models of complex software and hardware systems. A Markov analysis tool can be used during verification processes of models of avionics systems.
A. A. Karnov, S. V. Zelenov
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Attainability for Markov and Semi-Markov Chains
MathematicsWhen studying Markov chain models and semi-Markov chain models, it is useful to know which state vectors n, where each component ni represents the number of entities in the state Si, can be maintained or attained. This question leads to the definitions of maintainability and attainability for (time-homogeneous) Markov chain models.
Brecht Verbeken, Marie-Anne Guerry
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