SciML Open Source Scientific Machine Learning
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- Robust, Fast, and Parallel Global Sensitivity Analysis (GSA) in Julia
- 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, SDEs, DDEs, DAEs, etc.
- High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
- Implicit Layer Machine Learning via Deep Equilibrium Networks, O(1) backpropagation with accelerated convergence.
- Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
- A common interface for quadrature and numerical integration for the SciML scientific machine learning organization
SciMLExpectations.jl
PublicFast uncertainty quantification for scientific machine learning (SciML) and differential equations- Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions
- Surrogate modeling and optimization for scientific machine learning (SciML)
HighDimPDE.jl
PublicA Julia package for Deep Backwards Stochastic Differential Equation (Deep BSDE) and Feynman-Kac methods to solve high-dimensional PDEs without the curse of dimensionality- Reservoir computing utilities for scientific machine learning (SciML)
Catalyst.jl
PublicChemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.ModelingToolkit.jl
PublicAn acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations- CellMLToolkit.jl is a Julia library that connects CellML models to the Scientific Julia ecosystem.
- The Base interface of the SciML ecosystem
- A standard library of components to model the world and beyond
- The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
DelayDiffEq.jl
PublicDelay differential equation (DDE) solvers in Julia for the SciML scientific machine learning ecosystem. Covers neutral and retarded delay differential equations, and differential-algebraic equations.- Tools for building non-allocating pre-cached functions in Julia, allowing for GC-free usage of automatic differentiation in complex codes
SciMLStructures.jl
PublicBaseModelica.jl
Public- A simple domain-specific language (DSL) for defining differential equations for use in scientific machine learning (SciML) and other applications
- A common solve function for scientific machine learning (SciML) and beyond
- Solver for two-dimensional conservation equations using the finite volume method in Julia.
SurrogatesBase.jl
PublicQuasiMonteCarlo.jl
PublicLightweight 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)