Dependency Packages
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FMI.jl84FMI.jl is a free-to-use software library for the Julia programming language which integrates FMI (fmi-standard.org): load or create, parameterize, differentiate and simulate FMUs seamlessly inside the Julia programming language!
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OrbitalTrajectories.jl83OrbitalTrajectories.jl is a modern orbital trajectory design, optimisation, and analysis library for Julia, providing methods and tools for designing spacecraft orbits and transfers via high-performance simulations of astrodynamical models.
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JuLIP.jl83Julia Library for Interatomic Potentials
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FractionalDiffEq.jl80Solve Fractional Differential Equations using high performance numerical methods
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ClimaAtmos.jl79ClimaAtmos.jl is a library for building atmospheric circulation models that is designed from the outset to leverage data assimilation and machine learning tools. We welcome contributions!
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EasyModelAnalysis.jl79High level functions for analyzing the output of simulations
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AdvancedVI.jl78Implementation of variational Bayes inference algorithms
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ParameterizedFunctions.jl77A simple domain-specific language (DSL) for defining differential equations for use in scientific machine learning (SciML) and other applications
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SemanticModels.jl77A julia package for representing and manipulating model semantics
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Pathfinder.jl75Preheat your MCMC
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Modia3D.jl74Modeling and Simulation of 3D systems
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MultiScaleArrays.jl73A framework for developing multi-scale arrays for use in scientific machine learning (SciML) simulations
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OpenQuantumTools.jl72Julia toolkit for open quantum system simulation.
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IncrementalInference.jl72Clique recycling non-Gaussian (multi-modal) factor graph solver; also see Caesar.jl.
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ReactionMechanismSimulator.jl72The amazing Reaction Mechanism Simulator for simulating large chemical kinetic mechanisms
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HighDimPDE.jl71A Julia package for Deep Backwards Stochastic Differential Equation (Deep BSDE) and Feynman-Kac methods to solve high-dimensional PDEs without the curse of dimensionality
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RigidBodySim.jl71Simulation and visualization of articulated rigid body systems in Julia
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IonSim.jl71A simple tool for simulating trapped ion systems
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TuringGLM.jl71Bayesian Generalized Linear models using `@formula` syntax.
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DIVAnd.jl70DIVAnd performs an n-dimensional variational analysis of arbitrarily located observations
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QuantumCumulants.jl70Generalized mean-field equations in open quantum systems
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Turkie.jl68Turing + Makie = Turkie
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TaylorDiff.jl68Taylor-mode automatic differentiation for higher-order derivatives
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ODINN.jl68Global glacier model using Universal Differential Equations for climate-glacier interactions
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DiffEqUncertainty.jl65Fast uncertainty quantification for scientific machine learning (SciML) and differential equations
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WorldDynamics.jl65An open-source framework written in Julia for global integrated assessment models.
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SciMLExpectations.jl65Fast uncertainty quantification for scientific machine learning (SciML) and differential equations
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PETLION.jl65High-performance simulations of the Porous Electrode Theory for Li-ion batteries
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RoME.jl64Robot Motion Estimate: Tools, Variables, and Factors for SLAM in robotics; also see Caesar.jl.
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DiffEqNoiseProcess.jl63A library of noise processes for stochastic systems like stochastic differential equations (SDEs) and other systems that are present in scientific machine learning (SciML)
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StockFlow.jl63-
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ModelPredictiveControl.jl63An open source model predictive control package for Julia.
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SimpleNonlinearSolve.jl63Fast and simple nonlinear solvers for the SciML common interface. Newton, Broyden, Bisection, Falsi, and more rootfinders on a standard interface.
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TaylorModels.jl63Rigorous function approximation using Taylor models in Julia
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JutulDarcy.jl62Darcy flow and reservoir simulator based on Jutul.jl
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AtomicGraphNets.jl62Atomic graph models for molecules and crystals in Julia
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CellMLToolkit.jl62CellMLToolkit.jl is a Julia library that connects CellML models to the Scientific Julia ecosystem.
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OptimalControl.jl62Model and solve optimal control problems in Julia
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Conductor.jl61Choo-choo
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DiffEqParamEstim.jl61Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions
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