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.

Base functionality library for QuantumOptics.jl

A package for Gaussian random field generation in Julia

A collection of tools for chemometrics and machine learning written in Julia.

Visualization for Flux.Chain neural networks

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

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

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A package for performing Singular Spectrum Analysis (SSA) and time-series decomposition

An open source model predictive control package for Julia.

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

Flexible and efficient persistent homology computation.

Read R data files from Julia

Atomic graph models for molecules and crystals in Julia

Pull data from Federal Reserve Economic Data (FRED) directly into 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

Julia package for solving singular integral equations

A General Approach to Seismic Inversion Problems using Automatic Differentiation

Julia Kubernetes Client

MultiJuMP enables the user to easily run multiobjective optimisation problems and generate Pareto fronts.

Choo-choo

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

Conic Augmented Lagrangian Interior-Point SOlver

Distributed Julia arrays using the MPI protocol

Dithering algorithms in Julia.

Julia backend for Plotly Dash

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

Automated Bayesian model discovery for time series data

Functions useful when using Pluto in teaching.

Use Optim to train Flux models and visualize loss landscapes

Compositional data analysis in Julia

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 high functioning package detective.

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

Julia framework for spatial ecology - data types and utilities