SaaSHub helps you find the best software and product alternatives Learn more →
Top 6 Julia neural-ode Projects
-
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
-
SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
-
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.
-
DiffEqBase.jl
The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
-
-
DiffEqGPU.jl
GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem
-
Julia neural-ode discussion
Julia neural-ode related posts
-
Machine learning and black box numerical solver[D]
-
Accurate and Efficient Physics-Informed Learning Through Differentiable Simulation - Chris Rackauckas (ASA Statistical Computing & Graphics Sections)
-
Why Fortran is easy to learn
-
[R] New directions in Neural Differential Equations
-
JuliaSim - Simulating Reality (new product by Julia Computing)
-
Rust vs Fortran
-
Odd Behavior: Neural network hybrid differential equation example
-
A note from our sponsor - SaaSHub
www.saashub.com | 13 Jan 2025
Index
What are some of the best open-source neural-ode projects in Julia? This list will help you:
Project | Stars | |
---|---|---|
1 | DiffEqFlux.jl | 875 |
2 | SciMLSensitivity.jl | 333 |
3 | DiffEqBase.jl | 320 |
4 | ComponentArrays.jl | 301 |
5 | DiffEqGPU.jl | 284 |
6 | BoundaryValueDiffEq.jl | 46 |