Stars
Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.
A public MuSpAn page for community discussions and issue reporting.
A Julia package for the computation of hard, theoretically guaranteed bounds on the moments of jump-diffusion processes with polynomial data
Network analysis algorithms for reaction networks modeled using Catalyst.jl
Symbolic-Numeric Neural DAEs and Universal Differential Equations for Automating Scientific Machine Learning (SciML)
A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs…
Lightweight and easy generation of quasi-Monte Carlo sequences with a ton of different methods on one API for easy parameter exploration in scientific machine learning (SciML)
Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable i…
Robust, Fast, and Parallel Global Sensitivity Analysis (GSA) in Julia
Award winning software library for nonlinear dynamics and nonlinear timeseries analysis
A Julia package for probability distributions and associated functions.
A benchmarking framework for the Julia language
The Statistics stdlib that ships with Julia.
Random Number Generators for the Julia Language.
Powerful convenience for Julia visualizations and data analysis
Pkg - Package manager for the Julia programming language
High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.
A library of data interpolation and smoothing functions
A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers