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

High-performance simulations of the Porous Electrode Theory for Li-ion batteries

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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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

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.

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

Atomic graph models for molecules and crystals in Julia

Darcy flow and reservoir simulator based on Jutul.jl

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

Choo-choo

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.

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

Definition of dynamical systems and integrators for DynamicalSystems.jl

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

Robust, Fast, and Parallel Global Sensitivity Analysis (GSA) in Julia

Trajectory Optimization for Robot Arms

A few preconditioners for iterative solvers.

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.

Finds relationships between the parameters of a mathematical model

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

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

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

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

Quantum Algorithms for solving differential equations

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

Reachability analysis for closed-loop control systems in Julia

Boundary value problem (BVP) solvers for scientific machine learning (SciML)

Experimental framework for automatic differentiation finite-volume simulators

A Petri net modeling framework for the Julia programming language

A suite of tools for solving Nonlinear Schrodinger equations via higher-order algorithms and Darboux transformations.

Methods for computational information geometry