Leibniz MMS Days 2020 - Abstract
NetworkDynamics.jl has been developed at PIK to facilitate modeling and analysis of large, inhomogeneous, networked systems such as power grids. It provides a convenient interface to the fully-featured solver suite DifferentialEquations.jl. The programming language julia is the perfect framework for this package since it can be used like a scripting language for protoyping while matching the speed of FORTRAN and C when writing optimized code. In this talk we introduce the basic constructors of NetworkDynamics.jl and showcase potential applications ranging from neurodynamics to epidemic spreading. We conclude with a brief outlook to planned features such as support for stochastic and delay differential equations and integration with the machine learning environment Flux.jl.