Search Results for author: Terrence Sejnowski

Found 3 papers, 2 papers with code

Physics-based machine learning for modeling stochastic IP3-dependent calcium dynamics

no code implementations10 Sep 2021 Oliver K. Ernst, Tom Bartol, Terrence Sejnowski, Eric Mjolsness

We present a machine learning method for model reduction which incorporates domain-specific physics through candidate functions.

Deep Learning Moment Closure Approximations using Dynamic Boltzmann Distributions

1 code implementation28 May 2019 Oliver K. Ernst, Tom Bartol, Terrence Sejnowski, Eric Mjolsness

Moment closure methods are used to approximate a subset of low order moments by terminating the hierarchy at some order and replacing higher order terms with functions of lower order ones.

Learning Dynamic Boltzmann Distributions as Reduced Models of Spatial Chemical Kinetics

1 code implementation2 Mar 2018 Oliver K. Ernst, Thomas Bartol, Terrence Sejnowski, Eric Mjolsness

Finding reduced models of spatially-distributed chemical reaction networks requires an estimation of which effective dynamics are relevant.

Biological Physics Statistical Mechanics

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