SciML / SciMLSensitivity.jlLinks
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.
☆355Updated this week
Alternatives and similar repositories for SciMLSensitivity.jl
Users that are interested in SciMLSensitivity.jl are comparing it to the libraries listed below
Sorting:
- Linear operators for discretizations of differential equations and scientific machine learning (SciML)☆283Updated 2 years ago
- High accuracy derivatives, estimated via numerical finite differences (formerly FDM.jl)☆306Updated 7 months ago
- Documentation for the DiffEq differential equations and scientific machine learning (SciML) ecosystem☆304Updated last month
- The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML…☆336Updated this week
- A Julia Basket of Hand-Picked Krylov Methods☆417Updated 2 weeks ago
- Data driven modeling and automated discovery of dynamical systems for the SciML Scientific Machine Learning organization☆418Updated last month
- Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax),…☆328Updated this week
- Solution of nonlinear multiphysics partial differential equation systems using the Voronoi finite volume method☆261Updated this week
- GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem☆304Updated last month
- A Julia package to perform Bifurcation Analysis☆332Updated last week
- forward and reverse mode automatic differentiation primitives for Julia Base + StdLibs☆454Updated last month
- Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem☆286Updated last month
- Fast jacobian computation through sparsity exploitation and matrix coloring☆251Updated last month
- Automatic Finite Difference PDE solving with Julia SciML☆178Updated last month
- Fast non-allocating calculations of gradients, Jacobians, and Hessians with sparsity support☆267Updated 5 months ago
- High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity …☆269Updated 2 weeks ago
- LinearSolve.jl: High-Performance Unified Interface for Linear Solvers in Julia. Easily switch between factorization and Krylov methods, a…☆261Updated 2 weeks ago
- Package for writing high-level code for parallel high-performance stencil computations that can be deployed on both GPUs and CPUs☆348Updated this week
- Reverse Mode Automatic Differentiation for Julia☆377Updated 3 months ago
- Iterative algorithms for solving linear systems, eigensystems, and singular value problems☆416Updated 7 months ago
- Taylor polynomial expansions in one and several independent variables.☆357Updated last month
- A common interface for quadrature and numerical integration for the SciML scientific machine learning organization☆236Updated last month
- Arrays with arbitrarily nested named components.☆321Updated 3 weeks ago
- Julia package for function approximation☆554Updated 2 months ago
- Robust, modular and efficient implementation of advanced Hamiltonian Monte Carlo algorithms☆298Updated last week
- Surrogate modeling and optimization for scientific machine learning (SciML)☆345Updated 3 months ago
- Simple curve fitting in Julia☆352Updated 3 months ago
- Root finding functions for Julia☆380Updated 3 weeks ago
- Tools for building fast, hackable, pseudospectral partial differential equation solvers on periodic domains☆209Updated last month
- Julia package for orthogonal polynomial transforms☆270Updated last month