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Hello everybody,

the repositories associated to this profile are dedicated to making mathematical optimization more accessible. They investigate and showcase ways to use classical optimization methods like linear, semidefinite, stochastic, mixed integer, and dynamic pogramming for real world applications. The goal is to offer

  • an easy drag and drop interface for optimization problems
  • solutions to typical problems from optimal design, optimal estimation, optimal control
  • easy integration of optimization into production and planning processes

The code is mostly in Python and employs open source solvers. Feel free to contribute and improve the impact powerful and free optimization has on everyday life!

Personally my background is in Hilbert spaces and stochastic modelling but lately I am increasingly employing methods from operations research and I am looking to expand my knowledge of combinatorial optimizaton techniques. You can contact me at [email protected].

All the best, Jemil

Atlas optimization's Projects

atlasopt icon atlasopt

Solution procedures and a simple interface for mathematical optimization

atlasopt_wip icon atlasopt_wip

A diverse collection of projects that are work in progress. Spans a range of topics from machine learning and optimization.

calipy icon calipy

Deep Instrument models for geodesy

machine_learning icon machine_learning

A collection of projects dealing with machine learning; both for selfmade models made in torch, pyro, stablebaselines andand making use of openai's api

optimization icon optimization

A collection of projects dealing with mathematical programming of the convex and integer type

stochastic_modelling icon stochastic_modelling

A collection of projects dealing with stochastic modelling and uncertainty quantification

tutorials icon tutorials

A collection of tutorials dealing with stochastic modelling, optimization, and machine learning

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