Causal inference, graphical models and structure learning in Julia

Tools for the exploration of chaos and nonlinear dynamics

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.

A package for binary and continuous, single and multi-material, truss and continuum, 2D and 3D topology optimization on unstructured meshes using automatic differentiation in Julia.

A Julia package for solving systems of polynomials via homotopy continuation.

Kernel density estimators for Julia

Boosted trees in Julia

Fast, general-purpose interactive applications for complex systems

Julia package to run Dynamic Power System simulations. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab.

Polyhedral Computation Interface

Julia hybrid constraint programming solver enhanced by a reinforcement learning driven search.

Enabling StaticCompiler.jl-based compilation of (some) Julia code to standalone native binaries by avoiding GC allocations and llvmcall-ing all the things!

Geographical plotting utilities for Makie.jl

Graph-related recipes to be used with Plots.jl

Basic Geometry Types

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

Causal, Higher-Order, Probabilistic Programming

Core functionality for the MLJ machine learning framework

Reverse-mode automatic differentiation in Julia

Automatic Finite Difference PDE solving with Julia SciML

Implementation of domain-specific language (DSL) for dynamic probabilistic programming

Geophysical fluid dynamics pseudospectral solvers with Julia and FourierFlows.jl.

Automatic differentiation of Distributions using Tracker, Zygote, ForwardDiff and ReverseDiff

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

Differentiable RayTracing in Julia

A Julia framework for invertible neural networks

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Algorithms for quantifying associations, independence testing and causal inference from data.

Algorithms for quantifying associations, independence testing and causal inference from data.

Finite Element tools in Julia

A Julia package for strided array views and efficient manipulations thereof

Simple, fast, column-based storage for data analysis in Julia

Load and create NetCDF files in Julia

Wrapping deep learning models from the package Flux.jl for use in the MLJ.jl toolbox

A development environment for robust and global optimization

Package for Simulation, Tomography and Analysis of Quantum Computers

A high level API for GDAL - Geospatial Data Abstraction Library

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Build and simulate jump equations like Gillespie simulations and jump diffusions with constant and state-dependent rates and mix with differential equations and scientific machine learning (SciML)