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29 search results found
Differentialequations.jl
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2,689
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.
Modelingtoolkit.jl
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1,292
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
Scimltutorials.jl
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698
Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
Diffeqpy
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456
Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization
Catalyst.jl
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402
Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.
Scimlsensitivity.jl
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291
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
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282
The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
Scimlbenchmarks.jl
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279
Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
Diffeqoperators.jl
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279
Linear operators for discretizations of differential equations and scientific machine learning (SciML)
Diffeqgpu.jl
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261
GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem
Diffeqdocs.jl
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251
Documentation for the DiffEq differential equations and scientific machine learning (SciML) ecosystem
Stochasticdiffeq.jl
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229
Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem
Jumpprocesses.jl
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127
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)
Diffeqr
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127
Solving differential equations in R using DifferentialEquations.jl and the SciML Scientific Machine Learning ecosystem
Diffeqbayes.jl
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119
Extension functionality which uses Stan.jl, DynamicHMC.jl, and Turing.jl to estimate the parameters to differential equations and perform Bayesian probabilistic scientific machine learning
Scimlbase.jl
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111
The Base interface of the SciML ecosystem
Modelingtoolkitstandardlibrary.jl
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89
A standard library of components to model the world and beyond
Diffeqcallbacks.jl
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77
A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers
Bridge.jl
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77
A statistical toolbox for diffusion processes and stochastic differential equations. Named after the Brownian Bridge.
Multiscalearrays.jl
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69
A framework for developing multi-scale arrays for use in scientific machine learning (SciML) simulations
Diffeqnoiseprocess.jl
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61
A library of noise processes for stochastic systems like stochastic differential equations (SDEs) and other systems that are present in scientific machine learning (SciML)
Diffeqparamestim.jl
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60
Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions
Diffeqproblemlibrary.jl
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51
A library of premade problems for examples and testing differential equation solvers and other SciML scientific machine learning tools
Sciml.ai
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48
The SciML Scientific Machine Learning Software Organization Website
Diffeqdevtools.jl
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46
Benchmarking, testing, and development tools for differential equations and scientific machine learning (SciML)
Scimlworkshop.jl
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34
Workshop materials for training in scientific computing and scientific machine learning
Steadystatediffeq.jl
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25
Solvers for steady states in scientific machine learning (SciML)
Diffeqfinancial.jl
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23
Differential equation problem specifications and scientific machine learning for common financial models
Bridgediffeq.jl
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5
A thin wrapper over Bridge.jl for the SciML scientific machine learning common interface, enabling new methods for neural stochastic differential equations (neural SDEs)
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