8 citations · 11 across the 4 of their papers we have counts for
4 papers
Physics-based machine learning for modeling stochastic IP3-dependent calcium dynamics
Oliver K. Ernst, Tom Bartol, Terrence Sejnowski +1
We present a machine learning method for model reduction which incorporates domain-specific physics through candidate functions. Our method estimates an effective probability distr…
Deep Learning Moment Closure Approximations using Dynamic Boltzmann Distributions
Oliver K. Ernst, Tom Bartol, Terrence Sejnowski +1
The moments of spatial probabilistic systems are often given by an infinite hierarchy of coupled differential equations. Moment closure methods are used to approximate a subset of…
Reference Type Logic Variables in Constraint-logic Object-oriented Programming
Jan C. Dageförde
Constraint-logic object-oriented programming, for example using Muli, facilitates the integrated development of business software that occasionally involves finding solutions to co…
Learning Dynamic Boltzmann Distributions as Reduced Models of Spatial Chemical Kinetics
Oliver K. Ernst, Thomas Bartol, Terrence Sejnowski +1
Finding reduced models of spatially-distributed chemical reaction networks requires an estimation of which effective dynamics are relevant. We propose a machine learning approach t…