Julia bindings to Vega

Proximal Augmented Lagrangian solver for solving multiperiod contingency-constrained ACOPF

Medically-informed data preprocessing for machine learning

Package to map SPH particle data to a cartesian grid

Simple linear and nonlinear solvers in Julia

A Julia package to represent strided views over a parent DenseArray

Julia bindings for OptimPack, a library for solving large scale optimization problems

Power spectra on the masked sky

Core utilities for PopGen.jl, including the PopData type and file IO

Many-body objects for quantum computing: a Julia implementation

A lightweight Julia package to plot a density function for a given set of values with known uncertainties.

Test Cases for Regularized Optimization

A few extra distributions used in survival analysis

Pareto-related recipes to be used with Plots.jl

Ocean components for the PALEO biogeochemical framework

Stability Tools for Threshold Vector Autoregressive Models

A julia package for automatic finite size scaling.

Julia package for performing tensor contractions on distributed machines

Read and write IAEA phase space files

Data types for signals of radiation detectors

Computing the Riemann Theta function in Julia

[DEPRECATED: rendered useless by MathOptInterface.Bridges] A MathOptInterface extension for Semidefinite programming solvers

A Julia package for solving Riemann–Hilbert problems

Julia wrapper for TBLIS with TensorOperations.jl

TrainRun.jl will take a user-defined train and a path as an input for a train run calculation. It can calculate the train run as a time-efficient or energy-efficient operation mode. The results can then be used within the Julia environment.

Example environments and tools for the TrajectoryGamesBase interface.

Implement the rock sample problem using POMDPs.jl

Generate power law noise, in Julia.

Finds pole of inaccessibility for a given polygon. Based on Vladimir Agafonkin's https://github.com/mapbox/polylabel

Value-at-Risk for Julia

A dynamically-structured matrix population model

Bayesian Safety Signal Detection in Julia

Runge-Kutta Methods in Julia

More zeros than you can shake a stick at

Optimally tuned ridge regression when features can be partitioned into groups.

Implementation of The Cannon (Ness+ '15), a data-driven model for stellar spectra

Allow Markdown to be hidden and revealed in Jupyter

A Julia interface to the SDPT3 solver

URDF and meshes for the NASA Valkyrie robot

Structs backed by pointers, to make working with custom (e.g. bump) allocators easier.