Andrew Rosemberg's Projects
forward and reverse mode automatic differentiation primitives for Julia Base + StdLibs
Solutions of Cryptoanalysis problems
Package for building decision rules in multistage stochastic problems.
Differentiating convex optimization programs w.r.t. program parameters
FinancialTimeSeriesAnalysis
A Julia/JuMP Package for Hydrothermal economic dispatch Optimization
Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
Learning to optimize (L2O) package that provides basic functionalities to help fit proxy models for optimization.
Solver de: Andrew
NLopt wrapper in Nonconvex.jl.
Package for identifying optimal bids.
Extension for dealing with parameters
Portfolio optimization
A Julia/JuMP Package for Power Network Optimization
Julia for optimization simulation and modeling of PowerSystems
Data structures in Julia to enable power systems analysis.
Stochastic Dual Dynamic Programming in Julia
Strategy simulation for simple games.