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Mathematical Biosciences and Engineering : MBE
|
November 20, 2013
Preface
Susanne Ditlevsen, Petr Lansky
Plos One
|
May 16, 2019
Neural decoding with visual attention using sequential Monte Carlo for leaky integrate-and-fire neurons
Kang Li, Susanne Ditlevsen
Statistics in Medicine
|
July 19, 2006
A comment on: statistical evaluation of biomarkers as surrogate endpoints: a literature review by C. J. Weir and R. J. Walley, Statistics in Medicine 2006; 25:183-203
Susanne Ditlevsen, Niels Keiding
Mathematical Biosciences and Engineering : MBE
|
April 24, 2016
Preface
Susanne Ditlevsen, Petr Lansky
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|
November 13, 2007
Parameters of stochastic diffusion processes estimated from observations of first-hitting times: application to the leaky integrate-and-fire neuronal model
Susanne Ditlevsen, Petr Lansky
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|
December 11, 2012
Only through perturbation can relaxation times be estimated
Susanne Ditlevsen, Petr Lansky
Journal of Mathematical Biology
|
May 25, 2012
The Morris-Lecar neuron model embeds a leaky integrate-and-fire model
Susanne Ditlevsen, Priscilla Greenwood
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|
February 9, 2005
Estimation of the input parameters in the Ornstein-Uhlenbeck neuronal model
Susanne Ditlevsen, Petr Lansky
Neural Computation
|
April 28, 2011
Firing variability is higher than deduced from the empirical coefficient of variation
Susanne Ditlevsen, Petr Lansky
Biological Cybernetics
|
May 23, 2008
A review of the methods for signal estimation in stochastic diffusion leaky integrate-and-fire neuronal models
Petr Lansky, Susanne Ditlevsen
Page
of 6
Search research articles
Search
Showing results (1-10 of 59) with videos related to
Sort By:
Page
of 6
Mathematical Biosciences and Engineering : MBE
|
November 20, 2013
Preface
Susanne Ditlevsen, Petr Lansky
Plos One
|
May 16, 2019
Neural decoding with visual attention using sequential Monte Carlo for leaky integrate-and-fire neurons
Kang Li, Susanne Ditlevsen
Statistics in Medicine
|
July 19, 2006
A comment on: statistical evaluation of biomarkers as surrogate endpoints: a literature review by C. J. Weir and R. J. Walley, Statistics in Medicine 2006; 25:183-203
Susanne Ditlevsen, Niels Keiding
Mathematical Biosciences and Engineering : MBE
|
April 24, 2016
Preface
Susanne Ditlevsen, Petr Lansky
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|
November 13, 2007
Parameters of stochastic diffusion processes estimated from observations of first-hitting times: application to the leaky integrate-and-fire neuronal model
Susanne Ditlevsen, Petr Lansky
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|
December 11, 2012
Only through perturbation can relaxation times be estimated
Susanne Ditlevsen, Petr Lansky
Journal of Mathematical Biology
|
May 25, 2012
The Morris-Lecar neuron model embeds a leaky integrate-and-fire model
Susanne Ditlevsen, Priscilla Greenwood
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|
February 9, 2005
Estimation of the input parameters in the Ornstein-Uhlenbeck neuronal model
Susanne Ditlevsen, Petr Lansky
Neural Computation
|
April 28, 2011
Firing variability is higher than deduced from the empirical coefficient of variation
Susanne Ditlevsen, Petr Lansky
Biological Cybernetics
|
May 23, 2008
A review of the methods for signal estimation in stochastic diffusion leaky integrate-and-fire neuronal models
Petr Lansky, Susanne Ditlevsen
Page
of 6