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Top 10 Julia Differentialequation Projects
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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.
Another up-and-coming solution is Julia's simulation ecosystem [1]. It is powered by the commercial organization behind the Julia programming language, which has received DARPA funding [2] to build out these tools. This ecosystem unifies researchers in numerical methods [3], scalable compute, and domain experts in modeling engineering systems (electrical, mechanical, etc.) I believe this is where simulation is headed.
[1] https://juliahub.com/products/juliasim
[2] https://news.ycombinator.com/item?id=26425659
[3] https://docs.sciml.ai/DiffEqDocs/stable/
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NeuralPDE.jl
Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
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DiffEqFlux.jl
Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
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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)
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SciMLSensitivity.jl
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.
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DiffEqBase.jl
The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
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DiffEqGPU.jl
GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem
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StochasticDiffEq.jl
Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem
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NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Julia Differentialequations discussion
Julia Differentialequations related posts
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2023 was the year that GPUs stood still
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Modern Numerical Solving methods
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Automatically install huge number of dependency?
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Why Fortran is a scientific powerhouse
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Startups are building with the Julia Programming Language
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Accurate and Efficient Physics-Informed Learning Through Differentiable Simulation - Chris Rackauckas (ASA Statistical Computing & Graphics Sections)
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from Wolfram Mathematica to Julia
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A note from our sponsor - SaaSHub
www.saashub.com | 20 Jan 2025
Index
What are some of the best open-source Differentialequation projects in Julia? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | DifferentialEquations.jl | 2,894 |
| 2 | NeuralPDE.jl | 1,022 |
| 3 | DiffEqFlux.jl | 875 |
| 4 | OrdinaryDiffEq.jl | 571 |
| 5 | SciMLSensitivity.jl | 333 |
| 6 | DiffEqBase.jl | 320 |
| 7 | ComponentArrays.jl | 303 |
| 8 | DiffEqGPU.jl | 284 |
| 9 | StochasticDiffEq.jl | 264 |
| 10 | BoundaryValueDiffEq.jl | 46 |
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