A Julia package for (continuous) stochastic processes
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Updated
Nov 29, 2017 - Julia
A Julia package for (continuous) stochastic processes
Julia package to simulate stochastic processes.
Examples of computational stochastic processes in Julia lang
A lightweight, efficient package for simulating stochastic processes on various domains.
A Julia package that provides high-level abstractions for simulating and deploying stochastic filters
Julia stochastic processes package.
A Julia package that provides (feedback) particle filters for nonlinear stochastic filtering and data assimilation problems
A Julia package for the computation of hard, theoretically guaranteed bounds on the moments of jump-diffusion processes with polynomial data
Efficiently generate Gaussian stochastic processes with heavy-tailed algebraic correlations.
Stochastic-like characteristics of arithmetic dynamical systems: the Collatz hailstone sequences
Julia Package for Generating Scenario Trees and Scenario Lattices for Multistage Stochastic Optimization
Tools to generate and study moment equations for any chemical reaction network using various moment closure approximations
Julia package to facilitate the construction of JumpProblems on graphs.
A lightweight framework to enable hierarchical, heterogeneous dynamical systems co-integration. Batteries included!
Computes the boundary crossing probability for a general diffusion process and time-dependent boundary.
Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.
Piecewise Deterministic Markov Processes in Julia
Suite of simulations of spatio-temporal early warning signals of stochastic and deterministic dynamical systems
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