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

Sequential Monte Carlo algorithm for approximation of posterior distributions.

Generalized mean-field equations in open quantum systems

Econometrics in Julia

Taylor-mode automatic differentiation for higher-order derivatives

Restricted Boltzmann Machines in Julia

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

Turing + Makie = Turkie

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

Hyperparameter optimization algorithms for use in the MLJ machine learning framework

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

Integrated Assessment Modeling Framework

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

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

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

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

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

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

Base functionality library for QuantumOptics.jl

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.

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

Atomic graph models for molecules and crystals in Julia

A package for discrete-time optimal stochastic control

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

Choo-choo

Conic Augmented Lagrangian Interior-Point SOlver

Automated Bayesian model discovery for time series data

Use Optim to train Flux models and visualize loss landscapes

Compositional data analysis in Julia

Nonlinear optical pulse propagator

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

Expectation operators for Distributions.jl objects

Economic modeling in Julia

Implementation of advanced Sequential Monte Carlo and particle MCMC algorithms

Financial derivatives modeling and pricing in Julia.

Discrete event generation and simulation in Julia

A package with general tools for working with higher-dimensional tensor networks based on ITensor.

Robust and optimal design and analysis of linear control systems