SciML Open Source Scientific Machine Learning
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- Boundary value problem (BVP) solvers for scientific machine learning (SciML)
- A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers
sciml.ai
PublicThe SciML Scientific Machine Learning Software Organization Website- Reservoir computing utilities for scientific machine learning (SciML)
- 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
- Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.
- LinearSolve.jl: High-Performance Unified Interface for Linear Solvers in Julia. Easily switch between factorization and Krylov methods, add preconditioners, and all in one interface.
- A general interface for symbolic indexing of SciML objects used in conjunction with Domain-Specific Languages
- Fast and automatic structural identifiability software for ODE systems
- CellMLToolkit.jl is a Julia library that connects CellML models to the Scientific Julia ecosystem.
- Tools for building non-allocating pre-cached functions in Julia, allowing for GC-free usage of automatic differentiation in complex codes
- A simple domain-specific language (DSL) for defining differential equations for use in scientific machine learning (SciML) and other applications
- The Base interface of the SciML ecosystem
- A common solve function for scientific machine learning (SciML) and beyond
- Arrays with arbitrarily nested named components.
- Build and simulate jump equations like Gillespie simulations and jump diffusions with constant and state-dependent rates and mix with differential equations and scientific machine learning (SciML)
- Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
SurrogatesBase.jl
Public- 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.
- Lightweight and easy generation of quasi-Monte Carlo sequences with a ton of different methods on one API for easy parameter exploration in scientific machine learning (SciML)
NDInterpolations.jl
Public- This package contains a macro for converting expressions to use muladd calls and fused-multiply-add (FMA) operations for high-performance in the SciML scientific machine learning ecosystem
- Fast Poisson Random Numbers in pure Julia for scientific machine learning (SciML)
EllipsisNotation.jl
Public