Causal, Higher-Order, Probabilistic Programming

Core functionality for the MLJ machine learning framework

Sparse tensors in Julia and more! Datastructure-driven array programing language.

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

Automatic Finite Difference PDE solving with Julia SciML

A Julia package for statistical inference, data manipulation and visualization of phylogenetic networks

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

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

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

Lasso/Elastic Net linear and generalized linear models

A native Julia code for lattice QCD with dynamical fermions in 4 dimension.

Convenience meta-package to load essential packages for statistics

Quantlib implementation in pure Julia

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

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

Journal-style regression tables

System Identification toolbox, compatible with ControlSystems.jl

Beautiful and flexible vizualizations of high dimensional data

Uniform Manifold Approximation and Projection (UMAP) implementation in Julia

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.

A Julia implementation of basic tools for time series analysis compatible with incomplete data.

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

A Julia implementation of basic tools for time series analysis compatible with incomplete data.

A flexible neural net training library inspired by fast.ai

A Julia package for the creation, manipulation and analysis of the structure, dynamics and functions of multilayer graphs.

Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing

A package for Counterfactual Explanations and Algorithmic Recourse in Julia.

Climate science package for Julia

SymbolicNumericIntegration.jl: Symbolic-Numerics for Solving Integrals

Julia library for homological persistence

A Julia package to construct orthogonal polynomials, their quadrature rules, and use it with polynomial chaos expansions.

Causal.jl - A modeling and simulation framework adopting causal modeling approach.

State estimation, smoothing and parameter estimation using Kalman and particle filters.

A standard library of components to model the world and beyond

A package for time series data processing, classification, clustering, and prediction.

Equation-based modeling and simulations in Julia

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

A statistical toolbox for diffusion processes and stochastic differential equations. Named after the Brownian Bridge.

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.