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Eric Mjolsness

Showing results (11-20 of 35) with videos related to

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Machine Learning: Science and Technology|August 12, 2025
Graph prolongation convolutional networks: explicitly multiscale machine learning on graphs with applications to modeling of cytoskeletonCory B Scott, Eric Mjolsness
Plos One|April 27, 2021
Graph diffusion distance: Properties and efficient computationC B Scott, Eric Mjolsness
Bioinformatics (Oxford, England)|October 28, 2015
Pycellerator: an arrow-based reaction-like modelling language for biological simulationsBruce E Shapiro, Eric Mjolsness
BMC Systems Biology|July 29, 2010
Parameter inference for discretely observed stochastic kinetic models using stochastic gradient descentYuanfeng Wang, Scott Christley, Eric Mjolsness, et al.
Plos Computational Biology|December 30, 2006
Connectivity in the yeast cell cycle transcription network: inferences from neural networksChristopher E Hart, Eric Mjolsness, Barbara J Wold
Physical Biology|June 19, 2015
Model reduction for stochastic CaMKII reaction kinetics in synapses by graph-constrained correlation dynamicsTodd Johnson, Tom Bartol, Terrence Sejnowski, et al.
Frontiers in Plant Science|October 19, 2013
Using cellzilla for plant growth simulations at the cellular levelBruce E Shapiro, Elliot M Meyerowitz, Eric Mjolsness
The Journal of Chemical Physics|April 17, 2009
An exact accelerated stochastic simulation algorithmEric Mjolsness, David Orendorff, Philippe Chatelain, et al.
The Journal of Chemical Physics|July 25, 2018
Learning dynamic Boltzmann distributions as reduced models of spatial chemical kineticsOliver K Ernst, Thomas Bartol, Terrence Sejnowski, et al.
Arxiv|May 5, 2025
Synaptic Spine Head Morphodynamics from Graph Grammar Rules for Actin DynamicsMatthew Hur, Thomas Bartol, Padmini Rangamani, et al.
Pageof 4

Showing results (11-20 of 35) with videos related to

Sort By:
Pageof 4
Machine Learning: Science and Technology|August 12, 2025
Graph prolongation convolutional networks: explicitly multiscale machine learning on graphs with applications to modeling of cytoskeletonCory B Scott, Eric Mjolsness
Plos One|April 27, 2021
Graph diffusion distance: Properties and efficient computationC B Scott, Eric Mjolsness
Bioinformatics (Oxford, England)|October 28, 2015
Pycellerator: an arrow-based reaction-like modelling language for biological simulationsBruce E Shapiro, Eric Mjolsness
BMC Systems Biology|July 29, 2010
Parameter inference for discretely observed stochastic kinetic models using stochastic gradient descentYuanfeng Wang, Scott Christley, Eric Mjolsness, et al.
Plos Computational Biology|December 30, 2006
Connectivity in the yeast cell cycle transcription network: inferences from neural networksChristopher E Hart, Eric Mjolsness, Barbara J Wold
Physical Biology|June 19, 2015
Model reduction for stochastic CaMKII reaction kinetics in synapses by graph-constrained correlation dynamicsTodd Johnson, Tom Bartol, Terrence Sejnowski, et al.
Frontiers in Plant Science|October 19, 2013
Using cellzilla for plant growth simulations at the cellular levelBruce E Shapiro, Elliot M Meyerowitz, Eric Mjolsness
The Journal of Chemical Physics|April 17, 2009
An exact accelerated stochastic simulation algorithmEric Mjolsness, David Orendorff, Philippe Chatelain, et al.
The Journal of Chemical Physics|July 25, 2018
Learning dynamic Boltzmann distributions as reduced models of spatial chemical kineticsOliver K Ernst, Thomas Bartol, Terrence Sejnowski, et al.
Arxiv|May 5, 2025
Synaptic Spine Head Morphodynamics from Graph Grammar Rules for Actin DynamicsMatthew Hur, Thomas Bartol, Padmini Rangamani, et al.
Pageof 4