marta vanin's starred repositories
Clarabel.jl
Clarabel.jl: Interior-point solver for convex conic optimisation problems in Julia.
OPFLearn.jl
A Julia package that efficiently creates representative datasets for machine learning approaches to AC optimal power flow
PowerPlots.jl
Functions plot PowerModels networks
GameTheory.jl
Algorithms and data structures for game theory in Julia
Julia_Tutorials
Collection of tutorials on Julia
Transform-to-Open-Science
Transformation to Open Science
BilevelJuMP.jl
Bilevel optimization in JuMP
Parquet.jl
Julia implementation of Parquet columnar file format reader
power-grid-model
Python/C++ library for distribution power system analysis
scientific-visualization-book
An open access book on scientific visualization using python and matplotlib
The-Art-of-Linear-Algebra
Graphic notes on Gilbert Strang's "Linear Algebra for Everyone"
OptimizationModels
Optimization Models used in my e-book with the same title
ScoringEngineDemo.jl
Demo of a scoring engine. From data wrangling to model serving on docker
PowerModelsACDC.jl
A hybrid AC/DC OPF package based on PowerModels.jl
Hands-on-Design-Patterns-and-Best-Practices-with-Julia
Hands-On Design Patterns with Julia, published by Packt
Optimization.jl
Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.
PowerModelsDistributionStateEstimation.jl
A Julia Package for Power System State Estimation.
PowerModelsDistribution.jl
A Julia/JuMP Package for Unbalanced Power Network Optimization
Decision-Making-Under-Uncertainty
Decision making under uncertainty using the POMDPs.jl ecosystem taught by Robert Moss
CompatHelper.jl
Automatically update the [compat] entries for your Julia package's dependencies
FlexPlan.jl
Open-source Julia tool for transmission and distribution expansion planning considering storage and demand flexibility
Sundials.jl
Julia interface to Sundials, including a nonlinear solver (KINSOL), ODE's (CVODE and ARKODE), and DAE's (IDA) in a SciML scientific machine learning enabled manner