Fast uncertainty quantification for scientific machine learning (SciML) and differential equations

An open-source framework written in Julia for global integrated assessment models.

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Fast and simple nonlinear solvers for the SciML common interface. Newton, Broyden, Bisection, Falsi, and more rootfinders on a standard interface.

An open source model predictive control package for Julia.

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

Rigorous function approximation using Taylor models in Julia

Atomic graph models for molecules and crystals in Julia

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

Darcy flow and reservoir simulator based on Jutul.jl

Choo-choo

Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions

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.

Functions to compute omnidirectional landscape connectivity using circuit theory and the Omniscape algorithm.

Robust and optimal design and analysis of linear control systems

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.

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

Definition of dynamical systems and integrators for DynamicalSystems.jl

Library supporting the ArrayInterface.jl strided array interface.

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

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

A foolproof way of doing ML with GUI elements.

Trajectory Optimization for Robot Arms

A few preconditioners for iterative solvers.

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

Finds relationships between the parameters of a mathematical model

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

Logic Circuits from the Juice library

Neuroimaging in Julia

Pseudo Likelihood Maximization for protein in Julia

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

Partitioning images into meaningful regions

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

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)

Quantum Algorithms for solving differential equations

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Reachability analysis for closed-loop control systems in Julia