Flexible, overridable default field values

Tools for solving constrained dynamical systems

Gila implements free space, frequency domain, electromagnetic Green functions.

Support for Fourier-based spaces in ApproxFun

Equilibrium marriage market models.

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Spectrum calculation using the HITRAN database for Julia

Deconvolution algorithms popular in Cherenkov astronomy

PAGE-2020 - a Julia implementation of the PAGE Integrated Assessment Model

Built-in solvers for the GeoStats.jl framework

A decision-making framework for the cost-efficient design of experiments, balancing the value of acquired experimental evidence and incurred costs.

🧄 garlic growth simulation model

Differentiable wrapper for FrankWolfe.jl convex optimization routines

Parsers and processing for geoenergy data file formats in Julia.

Full field solutions of Poisson and Stokes problems in 1D, 2D and 3D. Full field solutions to other problems are welcome!

A Julia package for modelling Algorithmic Recourse Dynamics.

Package for fitting models according to the deep compartment modeling framework for pharmacometric applications.

A julia package to compute the Distribution of Relaxation Times (DRT) of a given set of impedance measurements.

Plot critical difference diagrams in Julia

Drawing functions for `SimpleGraphs`

Modular/extensible Julia library for Computer Adaptive Tests

Save videos from Julia

A non-linear Schrödinger equation solver for julia

Https://stevengogogo.github.io/FindSteadyStates.jl/dev

Forked Successor to github.com/JuliaFolds/FLoops.jl

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Differentiable acoustic ray tracers

Unfortunately, FMUs (fmi-standard.org) are not differentiable by design. To enable their full potential inside Julia, FMISensitivity.jl makes FMUs fully differentiable, regarding to: states and derivatives | inputs, outputs and other observable variables | parameters | event indicators | explicit time | state change sensitivity by event

A Makie theme

Toolbox for categorical time-series analysis.

Nonlinear diffusion problems in Julia

A thin wrapper over Bridge.jl for the SciML scientific machine learning common interface, enabling new methods for neural stochastic differential equations (neural SDEs)

Geometry optimization for molecular simulation

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An extension package of PowerModels.jl for Harmonic (Optimal) Power Network

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Bayesian addition to Flux.jl

Perform image hashing in julia

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Fast implementations of FastICA and DUET for blind source separation