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

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

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.

Boosted trees in Julia

Fast, general-purpose interactive applications for complex systems

Polyhedral Computation Interface

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

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

Reverse-mode automatic differentiation in Julia

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

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

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

Gaussian Process package based on data augmentation, sparsity and natural gradients

Predictive Uncertainty Quantification through Conformal Prediction for Machine Learning models trained in MLJ.

Plotting graphs with Makie

System Identification toolbox, compatible with ControlSystems.jl

Proximal algorithms for nonsmooth optimization in Julia

Complex neural network examples for Flux.jl

Algorithms and data structures for game theory in Julia

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

Flexible tables with ordered indices

A flexible neural net training library inspired by fast.ai

Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing

Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing

A package for Counterfactual Explanations and Algorithmic Recourse in Julia.

Divide and Conquer Linear Algebra

A Julia package for producing publication quality figures based on Makie.jl.

Toolbox for gradient-based and derivative-free non-convex constrained optimization with continuous and/or discrete variables.

Fast inference for Gaussian processes in problems involving time. Partly built on results from https://proceedings.mlr.press/v161/tebbutt21a.html

Interactive visualization tools for Julia

-

Word cloud generator in julia