Bayesian inference with probabilistic programming.

Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

🌊 Julia software for fast, friendly, flexible, ocean-flavored fluid dynamics on CPUs and GPUs

Julia Animations and Visualizations

Agent-based modeling framework in Julia

Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.

Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.

An extensible framework for geospatial data science and geostatistical modeling fully written in Julia

Computational geometry in Julia

Manifolds.jl provides a library of manifolds aiming for an easy-to-use and fast implementation.

A fast trajectory optimization library written in Julia

A differentiable physics engine for robotics

Julia implementation of various rigid body dynamics and kinematics algorithms

WebGL-based 3D visualizer in Julia

This library uses the LaTeX package pgfplots to produce plots.

Robust robotic localization and mapping, together with NavAbility(TM). Reach out to info@wherewhen.ai for help.

Julia implementations for different rotation parameterizations

Implementations of the models from the Statistical Rethinking book with Turing.jl

Differentiable collision detection for polytopes, capsules, cylinders, cones, spheres, and polygons.

Differentiable RayTracing in Julia

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A fast image augmentation library in Julia for machine learning.

Universal modeling and simulation of fluid mechanics upon machine learning. From the Boltzmann equation, heading towards multiscale and multiphysics flows.

Extension functionality which uses Stan.jl, DynamicHMC.jl, and Turing.jl to estimate the parameters to differential equations and perform Bayesian probabilistic scientific machine learning

Perceptually Uniform Colour Maps for Julia

Koma is a Pulseq-compatible framework to efficiently simulate Magnetic Resonance Imaging (MRI) acquisitions. The main focus of this package is to simulate general scenarios that could arise in pulse sequence development.

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Word cloud generator in julia

Fast contact-implicit model predictive control for robotic systems that make and break contact with their environments.

MADS: Model Analysis & Decision Support

Core functions for the Julia (2nd) edition of the text Fundamentals of Numerical Computation, by Driscoll and Braun.

Pure Julia implementations of single-pass object detection neural networks.

Dive deeper into your data with interactive graphics

Projective geometry for computer vision in Julia

High level functions for analyzing the output of simulations

Solid state detector field and charge drift simulation in Julia

Preheat your MCMC

Clique recycling non-Gaussian (multi-modal) factor graph solver; also see Caesar.jl.

The amazing Reaction Mechanism Simulator for simulating large chemical kinetic mechanisms

Simulation and visualization of articulated rigid body systems in Julia