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Top 6 Julia neural-differential-equation 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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SaaSHub
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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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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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Julia neural-differential-equations discussion
Julia neural-differential-equations related posts
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Automatically install huge number of dependency?
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from Wolfram Mathematica to Julia
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[D] ICLR 2022 RESULTS ARE OUT
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[N] Open Colloquium by Prof. Max Welling: "Is the next deep learning disruption in the physical sciences?"
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[D] What are some ideas that are hyped up in machine learning research but don't actually get used in industry (and vice versa)?
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[Research] Input Arbitrary PDE -> Output Approximate Solution
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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 neural-differential-equation projects in Julia? This list will help you:
# | Project | Stars |
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1 | DifferentialEquations.jl | 2,894 |
2 | NeuralPDE.jl | 1,022 |
3 | DiffEqFlux.jl | 875 |
4 | DiffEqBase.jl | 320 |
5 | DiffEqGPU.jl | 284 |
6 | BoundaryValueDiffEq.jl | 46 |