Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components

Optimization functions for Julia

Solve and estimate Dynamic Stochastic General Equilibrium models (including the New York Fed DSGE)

Universal neural differential equations with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods

Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.

Julia implementation of QuantEcon routines

Physics-Informed Neural Networks (PINN) and Deep BSDE Solvers of Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

Physics-Informed Neural Networks (PINN) and Deep BSDE Solvers of Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

Library for the numerical simulation of closed as well as open quantum systems.

Optical Simulation software

Probabilistic programming via source rewriting

An extensible framework for high-performance geostatistics in Julia

Julia version of selected functions in the R package `rethinking`. Used in the StatisticalRethinkingStan and StatisticalRethinkingTuring projects.

A Julia package for Gaussian Processes

Modeling and simulation of multidomain engineering systems

Local, global, and beyond optimization for scientific machine learning (SciML)

Data driven modeling and automated discovery of dynamical systems for the SciML Scientific Machine Learning organization

Density-functional toolkit

LowRankModels.jl is a julia package for modeling and fitting generalized low rank models.

Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem

StateSpaceModels.jl is a Julia package for time-series analysis using state-space models.

Robot toolkit: Towards non-parametric and parametric navigation solutions

Distributed High-Performance symbolic regression in Julia

Turing version of StatisticalRethinking models.

A Bayesian Analysis Toolkit in Julia

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 component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, and more for ODEs, SDEs, DDEs, DAEs, etc.

Hyperparameter optimization in Julia.

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

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

MADS: Model Analysis & Decision Support

Climate science package for Julia

Reservoir computing utilities for scientific machine learning (SciML)

System Identification toolbox for LTI systems, compatible with ControlSystems.jl

This package includes basic tools for time series analysis, compatible with incomplete data.

A julia package for representing and manipulating model semantics

Bayesian optimization for Julia

Algorithms that combine tensor network methods with automatic differentiation

Writing financial contracts in Julia

Incremental non-parametric (and parametric) solution to factor graphs