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

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

Robot Motion Estimate: Tools, Variables, and Factors for SLAM in robotics; also see Caesar.jl.

Visualization for Flux.Chain neural networks

An open source model predictive control package for Julia.

Rigorous function approximation using Taylor models in 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)

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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.

Darcy flow and reservoir simulator based on Jutul.jl

Julia package for solving singular integral equations

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

Atomic graph models for molecules and crystals in Julia

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

Choo-choo

Conic Augmented Lagrangian Interior-Point SOlver

Import, process and interpret geophysical data sets to be used in numerical models.

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.

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

A Power Flow Solver for GPUs in Julia

Nonlinear optical pulse propagator

Economic modeling in Julia

A bunch of fast text parsing tools

Distributed Data Parallel Training of Deep Neural Networks

Implementation of advanced Sequential Monte Carlo and particle MCMC algorithms

A Julia package for the Fourier analysis of Multivariate Data in the Frequency and Time-Frequency Domain

Data-parallelism on CUDA using Transducers.jl and for loops (FLoops.jl)

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.

Plotting extension library for CImGui.jl

Robust and optimal design and analysis of linear control systems

Julia interface to AMD/Radeon GPUs

Differentiable trajectory optimization in Julia.

Estimators for probabilities, entropies, and other complexity measures derived from data in the context of nonlinear dynamics and complex systems

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

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Definition of dynamical systems and integrators for DynamicalSystems.jl

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

Ambient Noise Cross-Correlation in Julia