MeshGraphNets.jl is a software package for the Julia programming language that provides an implementation of the MeshGraphNets framework by Google DeepMind for simulating mesh-based physical systems via graph neural networks.

From Semiconductor to TransistorLevel Modeling in Julia

Uniform interface for machine learning in Julia

An easy to use Julia framework for agent based modeling.

A high-performance library for gradient based quantum optimal control

Optimal experimental design of ODE and DAE systems in julia

Linearize dynamic economic models around their stochastic steady state

A SciML symbolic-numeric compiler tool for investigating functions in order to perform optimizations

Elastic foundation contact model for rigid body dynamics.

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Tools for robot visualization in Julia.

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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

Power spectra on the masked sky

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

Count operations for Julia code

Subspace Inference package for uncertainty analysis in deep neural networks and neural ordinary differential equations using Julia

A powerful, no code solution for control and systems engineering

Nested implementation selector

Differential Inequality Algorithms for Parametric ODEs

A Julia package containing GNC algorithms for autonomous aerospace systems

Dynamical systems identification

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Bounds and Relaxations of Parametric Differential Equations

Abstraction Layer for Dynamic Bounds

A package for the development and implementation of continuous-time policy gradient (CTPG) methods.

Automatically benchmark functions!

A Julia package for regression in the sphere based on Universal Differential Equations

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Valid Discrete-Time Methods for Relaxing pODEs

Visualization for the ConstrainedDynamics.jl package.

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A visualization package for the OpticSim Julia package

Simple predictive models for tumor growth, and tools to apply them to clinical data