SciML/JumpProcesses.jl

Build and simulate jump equations like Gillespie simulations and jump diffusions with constant and state-dependent rates and mix with differential equations and scientific machine learning (SciML)

Juliassaodestochasticdifferential-equationssdegillespiejump-diffusionneural-odescientific-machine-learningneural-differential-equationsscientific-mlscientific-aihybrid-differential-equationstochastic-jump-equationssciml
This is stars and forks stats for /SciML/JumpProcesses.jl repository. As of 02 May, 2024 this repository has 112 stars and 28 forks.

JumpProcesses.jl Note, JumpProcesses.jl is a renaming of DiffEqJump.jl, providing the current version of the latter. JumpProcesses.jl provides methods for simulating jump processes, known as stochastic simulation algorithms (SSAs), Doob's method, Gillespie methods, or Kinetic Monte Carlo methods across different fields of science. It also enables the incorporation of jump processes into hybrid jump-ODE and jump-SDE models, including jump diffusions. JumpProcesses is a component package in the SciML...
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