Dependency Packages
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DataDrivenDiffEq.jl405Data driven modeling and automated discovery of dynamical systems for the SciML Scientific Machine Learning organization
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IterativeSolvers.jl401Iterative algorithms for solving linear systems, eigensystems, and singular value problems
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Meshes.jl389Computational geometry in Julia
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Molly.jl389Molecular simulation in Julia
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BinaryBuilder.jl387Binary Dependency Builder for Julia
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StatisticalRethinking.jl386Julia package with selected functions in the R package `rethinking`. Used in the SR2... projects.
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MeasureTheory.jl386"Distributions" that might not add to one.
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DSP.jl379Filter design, periodograms, window functions, and other digital signal processing functionality
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TimeSeries.jl353Time series toolkit for Julia
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ProfileView.jl347Visualization of Julia profiling data
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Stheno.jl339Probabilistic Programming with Gaussian processes in Julia
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DiffEqSensitivity.jl329A 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.
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Surrogates.jl329Surrogate modeling and optimization for scientific machine learning (SciML)
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TrajectoryOptimization.jl329A fast trajectory optimization library written in Julia
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SciMLSensitivity.jl329A 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.
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Modia.jl321Modeling and simulation of multidomain engineering systems
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DiffEqBase.jl309The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
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GaussianProcesses.jl308A Julia package for Gaussian Processes
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Dojo.jl307A differentiable physics engine for robotics
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PowerSystems.jl306Data structures in Julia to enable power systems analysis. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab.
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Polynomials.jl303Polynomial manipulations in Julia
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BifurcationKit.jl301A Julia package to perform Bifurcation Analysis
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SDDP.jl295A JuMP extension for Stochastic Dual Dynamic Programming
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RigidBodyDynamics.jl287Julia implementation of various rigid body dynamics and kinematics algorithms
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DiffEqOperators.jl285Linear operators for discretizations of differential equations and scientific machine learning (SciML)
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DiffEqGPU.jl283GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem
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PowerSimulations.jl279Julia for optimization simulation and modeling of PowerSystems. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab.
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StateSpaceModels.jl271StateSpaceModels.jl is a Julia package for time-series analysis using state-space models.
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DimensionalData.jl271Named dimensions and indexing for julia arrays and other data
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Books.jl270Create books with Julia
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SymPy.jl268Julia interface to SymPy via PyCall
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GenX.jl267GenX: a configurable power system capacity expansion model for studying low-carbon energy futures. More details at : https://genx.mit.edu
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MCMCChain.jl266Types and utility functions for summarizing Markov chain Monte Carlo simulations
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MCMCChains.jl266Types and utility functions for summarizing Markov chain Monte Carlo simulations
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Bio.jl261[DEPRECATED] Bioinformatics and Computational Biology Infrastructure for Julia
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MonteCarloMeasurements.jl261Propagation of distributions by Monte-Carlo sampling: Real number types with uncertainty represented by samples.
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RxInfer.jl260Julia package for automated Bayesian inference on a factor graph with reactive message passing
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FastTransforms.jl259:rocket: Julia package for orthogonal polynomial transforms :snowboarder:
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StochasticDiffEq.jl248Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem
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LinearSolve.jl244LinearSolve.jl: High-Performance Unified Interface for Linear Solvers in Julia. Easily switch between factorization and Krylov methods, add preconditioners, and all in one interface.
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