#differential-equations (30 Repositories)
Ranked open-source repositories tagged with #differential-equations, scored by pull request acceptance likelihood and maintainer engagement velocity.
75.5%
77.5h
30 repositories tagged #differential-equations
SciML/DiffEqDocs.jl
Documentation for the DiffEq differential equations and scientific machine learning (SciML) ecosystem
SciML/ReservoirComputing.jl
Reservoir computing utilities for scientific machine learning (SciML)
SciML/ModelingToolkit.jl
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
SciML/LinearSolve.jl
LinearSolve.jl: High-Performance Unified Interface for Linear Solvers in Julia. Easily switch between factorization and Krylov methods, add preconditioners, and all in one interface.
SciML/PolyChaos.jl
A Julia package to construct orthogonal polynomials, their quadrature rules, and use it with polynomial chaos expansions.
SciML/ModelingToolkitStandardLibrary.jl
A standard library of components to model the world and beyond
SciML/OrdinaryDiffEq.jl
High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
cpmech/russell
Rust Scientific Library. ODE, DAE, and PDE solvers. Special functions (Bessel, Elliptic, Beta, Gamma, Erf). Linear algebra. Sparse solvers. Probability distributions. Tensor calculus. Numerical continuation.
SciML/Surrogates.jl
Surrogate modeling and optimization for scientific machine learning (SciML)
infiniteopt/InfiniteOpt.jl
An intuitive modeling interface for infinite-dimensional optimization problems.
SciML/DiffEqCallbacks.jl
A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers
SciML/Sundials.jl
Julia interface to Sundials, including a nonlinear solver (KINSOL), ODEs (CVODE and ARKODE), and DAEs (IDA)
SciML/ExponentialUtilities.jl
Fast and differentiable implementations of matrix exponentials, Krylov exponential matrix-vector multiplications ("expmv"), KIOPS, ExpoKit functions, and more. All your exponential needs in SciML form.
SciML/DataDrivenDiffEq.jl
Data driven modeling and automated discovery of dynamical systems for the SciML Scientific Machine Learning organization
SciML/NonlinearSolve.jl
High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.
SciML/NeuralPDE.jl
Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
SciML/Catalyst.jl
Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.
SciML/DifferentialEquations.jl
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.
SciML/DiffEqProblemLibrary.jl
A library of premade problems for examples and testing differential equation solvers and other SciML scientific machine learning tools
JuliaDynamics/NetworkDynamics.jl
Julia package for simulating Dynamics on Networks
SciML/FEniCS.jl
A scientific machine learning (SciML) wrapper for the FEniCS Finite Element library in the Julia programming language
SciML/DiffEqBayes.jl
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
SciML/DiffEqGPU.jl
GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem
SciML/ComponentArrays.jl
Arrays with arbitrarily nested named components.
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)
nathanaelbosch/ProbNumDiffEq.jl
Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing
JuliaReach/ReachabilityAnalysis.jl
Computing reachable states of dynamical systems in Julia
SciML/FluxNeuralOperators.jl
DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia
SciML/ODE.jl
Assorted basic Ordinary Differential Equation solvers for scientific machine learning (SciML). Deprecated: Use DifferentialEquations.jl instead.
LS-Lab/KeYmaeraX-release
KeYmaera X: An aXiomatic Tactical Theorem Prover for Hybrid Systems (release)