"Programming the Finite Element Method" by I M Smith, D V Griffiths and L Margetts

Julia Package for discrete-time linear Gaussian parametric filtering systems, namely KF, EKF, UKF, GM-PHD

Tools to generate and study moment equations for any chemical reaction network using various moment closure approximations

-

Direct and robust methods for outlier detection in linear regression

A full end-to-end modular software suite for radiative transfer and related atmospheric analysis

Julia library for deep reinforcement learning

Provides likelihood functions for Gaussian Processes.

Julia toolbox for underwater acoustic modeling

Methods for inferring undirected networks from data

Gmsh generated meshes for Gridap

Embedded finite element methods in Julia

Signal analysis toolbox for Julia

Create ensembles of machine learning models from scikit-learn, caret, and julia

A Julia package for constrained iterative LQR (iLQR)

Life Actuarial Maths

A library for graph analysis written Julia.

Implementations of single and multi-ellipsoid nested sampling

Julia package for ecosystem simulation

Quantile regression in Julia

Life Actuarial Maths

Flexible data augmentation library for machine and deep learning

Various Kalman Filters: KF, UKF, AUKF and their Square root variant

A Petri net modeling framework for the Julia programming language

-

Methods for computational information geometry

Arcade Learning Environment (ALE) wrapped as a Reinforce.jl environment

Tools to analyze and manipulate climate (spatiotemporal) data. Also used by ClimateTools and ClimatePlots

RHEOS - Open Source Rheology data analysis software

Unified contact simulaton and collision detection

SBML differential equation and chemical reaction model (Gillespie simulations) for Julia's SciML ModelingToolkit

Common functions in actuarial and financial routines

MarSwitching.jl: Julia package for Markov switching dynamic models :chart_with_upwards_trend:

The MultipleTesting package offers common algorithms for p-value adjustment and combination and more…

Data visualization in Julia

Sum-product networks in Julia.

A unified framework for skeletonization, morphological analysis, and connectivity analysis.

Convenient way to handle simple graphs and digraphs

Effortless Bayesian Deep Learning through Laplace Approximation for Flux.jl neural networks.

Publication quality regression and statistical tables