SciML / SciMLBenchmarksOutputLinks
SciML-Bench Benchmarks for Scientific Machine Learning (SciML), Physics-Informed Machine Learning (PIML), and Scientific AI Performance
☆22Updated this week
Alternatives and similar repositories for SciMLBenchmarksOutput
Users that are interested in SciMLBenchmarksOutput are comparing it to the libraries listed below
Sorting:
- No need to train, he's a smooth operator☆44Updated 6 months ago
- Common types and interface for discretizers of ModelingToolkit PDESystems.☆13Updated last week
- Proof of Concept: a C-callable GPU-enabled parallel 2-D heat diffusion solver written in Julia using CUDA, MPI and graphics☆24Updated 4 years ago
- Julia package for hierarchical matrices☆28Updated 7 months ago
- Efficient, Accurate, and Streamlined Training of Physics-Informed Neural Networks☆56Updated 2 months ago
- Physics-Enhanced Regression for Initial Value Problems☆20Updated last year
- Differentiable matrix factorizations using ImplicitDifferentiation.jl.☆30Updated last year
- A library of systems of partial differential equations, as defined with ModelingToolkit.jl in Julia☆28Updated 10 months ago
- High Oscillatory Ordinary Differential Equation Solver in Julia☆17Updated 6 months ago
- Implicit Runge-Kutta Gauss-Legendre 16th order (Julia)☆28Updated 2 months ago
- A package for multi-dimensional integration using monte carlo methods☆39Updated last year
- ☆31Updated 2 years ago
- Mulitprecision Arrays☆11Updated last week
- Tangent bundle, vector space and Submanifold definition☆50Updated 2 months ago
- Distributed Data Parallel Training of Deep Neural Networks☆57Updated last year
- A Julia repository for linear algebra with infinite matrices☆34Updated 2 months ago
- Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.☆22Updated last year
- ☆26Updated last year
- Machine learning from scratch in Julia☆31Updated 3 months ago
- GPU accelerated Particle Swarm Optimization☆24Updated 2 months ago
- Taylor-mode automatic differentiation for higher-order derivatives☆79Updated 2 months ago
- Symbolic-Numeric Neural DAEs and Universal Differential Equations for Automating Scientific Machine Learning (SciML)☆30Updated last week
- Examples for using ApproFun.jl☆25Updated 4 months ago
- Code for paper https://arxiv.org/abs/2306.07961☆53Updated 11 months ago
- ☆19Updated 6 months ago
- High-level model-order reduction to automate the acceleration of large-scale simulations☆39Updated this week
- Voronoi tesselations in Julia☆34Updated 2 years ago
- Integrating Neural Ordinary Differential Equations, the Method of Lines, and Graph Neural Networks☆18Updated last year
- Inspecting GPUs with Julia☆44Updated last year
- Discrete differential geometry on simplicial complexes☆26Updated 5 years ago