Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

Density-functional toolkit

System Identification toolbox, compatible with ControlSystems.jl

Universal modeling and simulation of fluid mechanics upon machine learning. From the Boltzmann equation, heading towards multiscale and multiphysics flows.

Global glacier model using Universal Differential Equations for climate-glacier interactions

Distributed Data Parallel Training of Deep Neural Networks

Robust and optimal design and analysis of linear control systems

Efficient, Accurate, and Streamlined Training of Physics-Informed Neural Networks

The automatically differentiable and GPU-compatible toolkit for CMB analysis.

A framework for composing and simulating multiphysics systems

A toolbox meant for aircraft design analyses.

A toolbox meant for aircraft design analyses.

Methods for computational information geometry

An interface for accelerated simulation of high-dimensional collisionless and electrostatic plasmas.

Fast approximate high-dimensional hierarchical Bayesian inference

Differentiable matrix factorizations using ImplicitDifferentiation.jl.

Implementations of Infinitesimal Continuous Normalizing Flows Algorithms in Julia

Symbolic-Numeric Universal Differential Equations for Automating Scientific Machine Learning (SciML)

Astrodynamics with units! Provides common astrodynamics calculations, plotting, and iterative Halo, Kepler, and Lambert solvers.

General Relativistic Orbital Dynamics in Julia

A general purpose numerical simulator supporting nested dynamical systems and a convenient macro-based data logger.

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.

A Julia package that implements a category of reaction (transportation) network-type dynamical systems.

Interface between ControlSystems and ModelingToolkit

A flexible toolkit for simulation based inference in Julia

Reduced basis methods for parametrised eigenproblems

Istope-enabled implementation of the LWF-BROOK90 hydrological model in Julia

Lightweight module of neural differential equations in Kinetic.jl

Optimal experimental design of ODE and DAE systems in julia

A Julia package for mapping qualitative data patterns to regions of a model's parameter space.

Next generation permafrost process modeling in the Julia programming language.

A Julia package for parameterized convex approximators including parameterized log-sum-exp (PLSE) network.

A package of FlightSims.jl family for ROS2.

A collection of chaotic ODEs.

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

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

Interface and Julia implementation of exchange-correlation functionals

Predefined environments and controllers for FlightSims.jl

A Julia package containing GNC algorithms for autonomous aerospace systems

Lightweight module for fusing physical and neural models