Physics-Informed Neural networks for Advanced modeling
Physics-Informed Neural networks for Advanced modeling - Published in JOSS (2023)
GlobalSensitivity.jl
GlobalSensitivity.jl: Performant and Parallel Global Sensitivity Analysis with Julia - Published in JOSS (2022)
ProbNumDiffEq.jl
ProbNumDiffEq.jl: Probabilistic Numerical Solvers for Ordinary Differential Equations in Julia - Published in JOSS (2024)
diffsol: Rust crate for solving differential equations
diffsol: Rust crate for solving differential equations - Published in JOSS (2026)
OwlDE
OwlDE: making ODEs first-class Owl citizens - Published in JOSS (2019)
amici
High-performance sensitivity analysis for large ordinary differential equation models
Catalyst
Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.
parpe
Parameter estimation for dynamical models using high-performance computing, batch and mini-batch optimizers, and dynamic load balancing.
reachabilityanalysis.jl
Computing reachable states of dynamical systems in Julia
Sundials
Julia interface to Sundials, including a nonlinear solver (KINSOL), ODE's (CVODE and ARKODE), and DAE's (IDA) in a SciML scientific machine learning enabled manner
best-of-ps
🏆 A weekly updated ranked list of popular open-source libraries and tools for Power System Analysis.
ModelingToolkit
An 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
DelayDiffEq
Delay differential equation (DDE) solvers in Julia for the SciML scientific machine learning ecosystem. Covers neutral and retarded delay differential equations, and differential-algebraic equations.
NeuralPDE
Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
SciMLBenchmarks
Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
ImplicitDiscreteSolve
High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
SBMLToolkit
SBML differential equation and chemical reaction model (Gillespie simulations) for Julia's SciML ModelingToolkit
JumpProcesses
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)
NeuroDiffEq
NeuroDiffEq: A Python package for solving differential equations with neural networks - Published in JOSS (2020)
DiffEqBase
The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
https://github.com/ami-iit/jaxsim
A differentiable physics engine and multibody dynamics library for control and robot learning.
SciMLSensitivity
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.
DifferentialEquations
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.
SteadyStateDiffEq
Solvers for steady states in scientific machine learning (SciML)
SciMLTutorials
Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
diffeqpy
Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization
DiffEqParamEstim
Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions
MultiScaleArrays
A framework for developing multi-scale arrays for use in scientific machine learning (SciML) simulations
DiffEqBayes
Extension functionality which uses Stan.jl, DynamicHMC.jl, and Turing.jl to estimate the parameters to differential equations and perform Bayesian probabilistic scientific machine learning
DiffEqPhysics
A library for building differential equations arising from physical problems for physics-informed and scientific machine learning (SciML)
DiffEqDevTools
Benchmarking, testing, and development tools for differential equations and scientific machine learning (SciML)
SciMLExpectations
Fast uncertainty quantification for scientific machine learning (SciML) and differential equations
https://github.com/bluescarni/heyoka.py
Python library for ODE integration via Taylor's method and LLVM
DASSL
Solves stiff differential algebraic equations (DAE) using variable stepsize backwards finite difference formula (BDF) in the SciML scientific machine learning organization
Adapode
Adaptive P/ODE numerics with Grassmann element TensorField assembly
sbml2julia
A tool to for optimizing parameters of ordinary differential equation (ODE) models. SBML2Julia translates a model from SBML/PEtab format into Julia for Mathematical Programming (JuMP), performs the optimization task and returns the results.
DiffEqCallbacks
A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers
BVProblemLibrary
A library of premade problems for examples and testing differential equation solvers and other SciML scientific machine learning tools
diffeqdocs.jl
Documentation for the DiffEq differential equations and scientific machine learning (SciML) ecosystem
pararealgpu.jl
A distributed and GPU-based implementation of the Parareal algorithm for parallel-in-time integration of equations of motion.
desolver
A Python library for solving Initial Value Problems using various numerical integration methods.
scimltutorialsoutput
Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
cvode_wrap
A wrapper around the cvode(S) ODE solver from sundials. Mirror of https://gitlab.inria.fr/InBio/Public/cvode-rust-wrap
https://github.com/avitase/libgravix2
A fast yet precise simulation of conservative, attractive forces acting on point-like particles embedded onto the surface of a unit sphere.
BridgeDiffEq
A thin wrapper over Bridge.jl for the SciML scientific machine learning common interface, enabling new methods for neural stochastic differential equations (neural SDEs)
SciMLWorkshop
Workshop materials for training in scientific computing and scientific machine learning
torchlaplace
Neural Laplace: Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.
https://github.com/a-herzog/numericalode
Numerical differential equation solver visualized the numerical solution of ode
moccasin
MOCCASIN translates basic ODE-based MATLAB models of biological processes into SBML format.
org.hipparchus:hipparchus
An efficient, general-purpose mathematics components library in the Java programming language