Results 231 to 240 of about 334,309 (266)
Beyond metaphor: quantitative reconstruction of Waddington landscape and exploration of cellular behavior. [PDF]
Brief BioinformHan Y, Chen B, Zhang J, Shang X.
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AI-Guided Inference of Morphodynamic Attractor-like States in Glioblastoma. [PDF]
Diagnostics (Basel)Volovăț SR +8 more
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β-Fractional [Formula: see text]-dimensional generalized KP model: nonlinear dynamical behaviors, analytical wave structures, bifurcation, and sensitivity analysis. [PDF]
Sci RepDemirbilek U +4 more
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Understanding Brain Functional Dynamics Through Neural Koopman Operator With Control Mechanism. [PDF]
IEEE Trans Med ImagingZhou Z, Dan T, Wu G.
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Allgemeines Statistisches Archiv, 2005 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Breitung, Jörg, Eickmeier, Sandra
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Current Eye Research, 2007
Quantitative understanding of tear dynamics may help in developing better ophthalmic drug delivery vehicles and dry eye treatments. This paper attempts to develop a comprehensive model that can predict the effect of physiological parameters on various issues related to tear dynamics.The model is based on mass balances of water and solutes such as ...
Heng, Zhu, Anuj, Chauhan
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Quantitative understanding of tear dynamics may help in developing better ophthalmic drug delivery vehicles and dry eye treatments. This paper attempts to develop a comprehensive model that can predict the effect of physiological parameters on various issues related to tear dynamics.The model is based on mass balances of water and solutes such as ...
Heng, Zhu, Anuj, Chauhan
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Proceedings of the 23rd international conference on Machine learning - ICML '06, 2006
A family of probabilistic time series models is developed to analyze the time evolution of topics in large document collections. The approach is to use state space models on the natural parameters of the multinomial distributions that represent the topics.
Blei, David M., Lafferty, John D.
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A family of probabilistic time series models is developed to analyze the time evolution of topics in large document collections. The approach is to use state space models on the natural parameters of the multinomial distributions that represent the topics.
Blei, David M., Lafferty, John D.
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WIREs Systems Biology and Medicine, 2010
AbstractActin monomers assemble into filaments that structurally support cells as well as drive membrane protrusion for cell movement. Within cells, some actin structures are very dynamic and turn over rapidly, while others are very stable. Even purified actin filament dynamics are complex, and researchers have often turned to mathematical models in ...
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AbstractActin monomers assemble into filaments that structurally support cells as well as drive membrane protrusion for cell movement. Within cells, some actin structures are very dynamic and turn over rapidly, while others are very stable. Even purified actin filament dynamics are complex, and researchers have often turned to mathematical models in ...
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Econometric Reviews, 2001
This paper introduces nonlinear dynamic factor models for various applications related to risk analysis. Traditional factor models represent the dynamics of processes driven by movements of latent variables, called the factors. Our approach extends this setup by introducing factors defined as random dynamic parameters and stochastic autocorrelated ...
Christian Gourieroux, Joanna Jasiak
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This paper introduces nonlinear dynamic factor models for various applications related to risk analysis. Traditional factor models represent the dynamics of processes driven by movements of latent variables, called the factors. Our approach extends this setup by introducing factors defined as random dynamic parameters and stochastic autocorrelated ...
Christian Gourieroux, Joanna Jasiak
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