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)

ORM layer for Genie.jl, the highly productive Julia web framework

A fast image augmentation library in Julia for machine learning.

Quantlib implementation in pure Julia

ConstraintSolver in Julia: Blog posts ->

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

Interactive display of images and movies

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

Fermi quantum chemistry program

Journal-style regression tables

A Julia interface to the CPLEX solver

System Identification toolbox, compatible with ControlSystems.jl

A solver for mixed-integer convex optimization

The Base interface of the SciML ecosystem

Uniform Manifold Approximation and Projection (UMAP) implementation in Julia

Proximal algorithms for nonsmooth optimization in Julia

Beautiful and flexible vizualizations of high dimensional data

Proximal operators 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

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

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

Technical analysis of financial time series in Julia

Library for finding the roots of a function using interval arithmetic

Improved thread management for background and nonuniform tasks in Julia. Docs at https://tro3.github.io/ThreadPools.jl

Algorithms and data structures for game theory in Julia

Complex neural network examples for Flux.jl

Julia package for simulating Dynamics on Networks

For working with dimensions of arrays by name

Differentiating convex optimization programs w.r.t. program parameters

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

Solve non-linear HJB equations.

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

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

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

Julia interface to gnuplot

Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing