A development environment for robust and global optimization

Package for Simulation, Tomography and Analysis of Quantum Computers

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)

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)

Read ONNX graphs in Julia

It slices, it dices, it splices!

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

Fermi quantum chemistry program

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

Plotting graphs with Makie

System Identification toolbox, compatible with ControlSystems.jl

The Base interface of the SciML ecosystem

Proximal algorithms for nonsmooth optimization in Julia

Algorithms from circuit theory to predict connectivity in heterogeneous landscapes

A differentiable simulator for scientific machine learning (SciML) with N-body problems, including astrophysical and molecular dynamics

A Julia package dedicated to simulating quantum many-body systems using Matrix Product States (MPS)

ODE integration using Taylor's method, and more, in Julia

Algorithms and data structures for game theory in Julia

Julia package for simulating Dynamics on Networks

Complex neural network examples for Flux.jl

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

Automatic differentiation of implicit functions

Solve non-linear HJB equations.

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

Arrays which also have a label for each element for easy scientific machine learning (SciML)

Flexible tables with ordered indices

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

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

Algebraic Multigrid in Julia

SymbolicNumericIntegration.jl: Symbolic-Numerics for Solving Integrals

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

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

Combinatorial optimization layers for machine learning pipelines

Equation-based modeling and simulations in Julia

A standard library of components to model the world and beyond

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