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20 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
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
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
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
Diffeqcallbacks.jl
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77
A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers
Multiscalearrays.jl
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69
A framework for developing multi-scale arrays for use in scientific machine learning (SciML) simulations
Diffeqparamestim.jl
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60
Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions
Delaydiffeq.jl
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53
Delay differential equation (DDE) solvers in Julia for the SciML scientific machine learning ecosystem. Covers neutral and retarded delay differential equations, and differential-algebraic equations.
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
Neurallaplace
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48
Neural Laplace: Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.
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)
Steadystatediffeq.jl
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25
Solvers for steady states in scientific machine learning (SciML)
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