Workshop materials for training in scientific computing and scientific machine learning
GitHub repository with 39 stars and 6 forks.
Language: Julia
Topics: adjoint, adjoint-method, adjoint-sensitivities, differential-equations, differential-equations-solvers, inverse-problems, ode, ode-solver, odeint, odes
2026-06-15: 39 stars and 6 forks.
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.
GitHub repository with 387 stars and 84 forks.
Trending score: 0.10; stars gained: +0; forks gained: +0.
Language: Julia
Topics: differentialequations, sensitivity-analysis, neural-ode, adjoint, backpropogation, neural-sde
The Julia Programming Language
GitHub repository with 48,854 stars and 5,790 forks.
Trending score: 2.25; stars gained: +11; forks gained: +0.
Language: Julia
Reusable array functionality for Julia's various GPU backends.
GitHub repository with 439 stars and 101 forks.
Trending score: 1.30; stars gained: +4; forks gained: +2.
Language: Julia
Topics: gpu, hacktoberfest, julia
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.
GitHub repository with 3,120 stars and 249 forks.
Trending score: 1.26; stars gained: +5; forks gained: -1.
Language: Julia
Topics: differential-equations, differentialequations, julia, ode, sde, dae
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
GitHub repository with 1,637 stars and 256 forks.
Trending score: 1.09; stars gained: +3; forks gained: +1.
Language: Julia
Topics: differential-equations, ode, dae, ordinary-differential-equations, pde, sde
GitHub repository with 16 stars and 2 forks.
Trending score: 1.02; stars gained: +6; forks gained: +0.
Language: Julia
Solid state detector field and charge drift simulation in Julia
GitHub repository with 165 stars and 54 forks.
Trending score: 0.95; stars gained: +3; forks gained: +0.
Language: Julia
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.
GitHub repository with 387 stars and 84 forks.
Trending score: 0.10; stars gained: +0; forks gained: +0.
Language: Julia
Topics: differentialequations, sensitivity-analysis, neural-ode, adjoint, backpropogation, neural-sde