Built-in solvers for the GeoStats.jl framework

Implementation of a GNSSReceiver

Statistical inference for Poisson Processes

Collection 3D visualization tools associated with the Caesar.jl and RoME.jl robot navigation packages

(Hierarchical) Phylogenetic Models in Julia

Prescribed flow models for testing cloud microphysics schemes.

Prescribed flow models for testing cloud microphysics schemes.

Equilibrium marriage market models.

Controllers for airborne wind energy systems

-

Julia package to provide reference European option prices for stochastic volatility models with a known characteristic function, such as the Heston stochastic volatility model.

A package for obtaining the effective time-averaged Lindbladian.

Tools for robot visualization in Julia.

Simulate EEG / ERP data with overlap, non-linear effects, multiple regression

ConceptualClimateModels.jl is a Julia package for creating and analysing conceptual models of climate, such as energy balance models, glaciation cycle models, or climate tipping models.

A Julia package for real-time audification of ODEs and SDEs

Nonnegative Tensor Factorization + k-means clustering and physics constraints for Unsupervised and Physics-Informed Machine Learning

Locally weighted regression solver for the GeoStats.jl framework

An extension package of PowerModels.jl for Harmonic (Optimal) Power Network

-

-

Modular/extensible Julia library for Computer Adaptive Tests

Package for fitting models according to the deep compartment modeling framework for pharmacometric applications.

Effective parallelism for power flow calculation

A toolkit for the quantum and classical Dicke model in Julia.

High performance hybrid Monte Carlo simulation

A julia package to compute the Distribution of Relaxation Times (DRT) of a given set of impedance measurements.

Drawing functions for `SimpleGraphs`

Generalized Estimating Equations (GEE) in Julia

Julia implementation of Factored Spectrally Transformed Linear Mixed Models

Quantum mechanical few body systems in Julia

Https://stevengogogo.github.io/FindSteadyStates.jl/dev

Unfortunately, FMUs (fmi-standard.org) are not differentiable by design. To enable their full potential inside Julia, FMISensitivity.jl makes FMUs fully differentiable, regarding to: states and derivatives | inputs, outputs and other observable variables | parameters | event indicators | explicit time | state change sensitivity by event

Nonlinear diffusion problems in Julia

Geometry optimization for molecular simulation

Differentiable acoustic ray tracers

Extension of PowerSimulations.jl to model Hydropower devices

Provides a general framework for implementing and performing Kernel Density Estimation

Variable Selection with Knockoffs

Solver for complemetarity-based dynamics.