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A library of noise processes for stochastic systems like stochastic differential equations (SDEs) and other systems that are present in scientific machine learning (SciML)

An open source model predictive control package for Julia.

Atomic graph models for molecules and crystals in Julia

A General Approach to Seismic Inversion Problems using Automatic Differentiation

CellMLToolkit.jl is a Julia library that connects CellML models to the Scientific Julia ecosystem.

Choo-choo

Implementation of various ensemble Kalman Filter data assimilation methods in Julia

Use Optim to train Flux models and visualize loss landscapes

Delay differential equation (DDE) solvers in Julia for the SciML scientific machine learning ecosystem. Covers neutral and retarded delay differential equations, and differential-algebraic equations.

A multi-dimensional, high performance deconvolution framework written in Julia Lang for CPUs and GPUs.

A Power Flow Solver for GPUs in Julia

Nonlinear optical pulse propagator

Economic modeling in Julia

FMIFlux.jl is a free-to-use software library for the Julia programming language, which offers the ability to place FMUs (fmi-standard.org) everywhere inside of your ML topologies and still keep the resulting model trainable with a standard (or custom) FluxML training process.

Robust and optimal design and analysis of linear control systems

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

Definition of dynamical systems and integrators for DynamicalSystems.jl

Dense and Sparse Least Squares Optimization

A Julia package for solving nonlinear differential equations using the harmonic balance method.

A hybrid AC/DC OPF package based on PowerModels.jl

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

Trajectory Optimization for Robot Arms

Julia package towards classical molecular modeling of nanoporous materials

Finds relationships between the parameters of a mathematical model

C-code generation and an interface between ControlSystems.jl and SymPy.jl

Implicit Layer Machine Learning via Deep Equilibrium Networks, O(1) backpropagation with accelerated convergence.

A library for building differential equations arising from physical problems for physics-informed and scientific machine learning (SciML)

Julia versions of the CompEcon routines by Miranda and Fackler.

A fast and flexible Structural Equation Modelling Framework

Geometric Numerical Integration in Julia

Julia package containing utilities intended for Time Series analysis.

A CPU- and GPU-friendly package for solving ordinary differential equations

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Benchmarking, testing, and development tools for differential equations and scientific machine learning (SciML)

Measure the distance between two spectra/signals using optimal transport and related metrics

Markov chain Monte Carlo solver for lattice spin systems implemented in Julialang

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Tools to generate and study moment equations for any chemical reaction network using various moment closure approximations