A Julia package for Deep Backwards Stochastic Differential Equation (Deep BSDE) and Feynman-Kac methods to solve high-dimensional PDEs without the curse of dimensionality

Inference of microbial interaction networks from large-scale heterogeneous abundance data

Bayesian Generalized Linear models using `@formula` syntax.

Sequential Monte Carlo algorithm for approximation of posterior distributions.

Generalized mean-field equations in open quantum systems

Econometrics in Julia

Turing + Makie = Turkie

Taylor-mode automatic differentiation for higher-order derivatives

Restricted Boltzmann Machines in Julia

Global glacier model using Universal Differential Equations for climate-glacier interactions

Everything you've never dreamed about measuring on ecological networks.

A comprehensive suite of coherent noise algorithms and composable tools for manipulating them.

Hyperparameter optimization algorithms for use in the MLJ machine learning framework

Integrated Assessment Modeling Framework

An open-source framework written in Julia for global integrated assessment models.

High-performance simulations of the Porous Electrode Theory for Li-ion batteries

Fast uncertainty quantification for scientific machine learning (SciML) and differential equations

Fast uncertainty quantification for scientific machine learning (SciML) and differential equations

Robot Motion Estimate: Tools, Variables, and Factors for SLAM in robotics; also see Caesar.jl.

Base functionality library for QuantumOptics.jl

A collection of tools for chemometrics and machine learning written in Julia.

A library of noise processes for stochastic systems like stochastic differential equations (SDEs) and other systems that are present in scientific machine learning (SciML)

Flexible and efficient persistent homology computation.

A package for discrete-time optimal stochastic control

CellMLToolkit.jl is a Julia library that connects CellML models to the Scientific Julia ecosystem.

Atomic graph models for molecules and crystals in Julia

Conic Augmented Lagrangian Interior-Point SOlver

Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions

Choo-choo

Automated Bayesian model discovery for time series data

Compositional data analysis in Julia

Use Optim to train Flux models and visualize loss landscapes

Nonlinear optical pulse propagator

A Julia package for creating publication-ready summary tables in HTML, docx, LaTeX and Typst

Economic modeling in Julia

Expectation operators for Distributions.jl objects

Implementation of advanced Sequential Monte Carlo and particle MCMC algorithms

Financial derivatives modeling and pricing in Julia.

Robust and optimal design and analysis of linear control systems

Differentiable trajectory optimization in Julia.