GeomScale

Sampling from high-dimensional convex polytopes is a fundamental problem with applications in statistics, machine learning, optimization, and systems...

This project explores the problem of estimating how the volume of a high-dimensional convex polytope changes under sequential constraint additions....

This project aims to develop a Benchmark Polytope Import Suite for the volesti library, enabling automated conversion of standard Linear Programming...

This project will implement a new volume-based approach for approximately counting linear extensions of partially ordered sets in volesti. The core...

Dingo is a Python library built on top of the C++ library volesti, primarily designed for sampling from convex polytopes, especially within the...

The proposed project aims to continue the implementation of the semidefinite pro- gramming (SDP) solver in the VolEsti library and to integrate it...

The project aims to implement the Markov Chain Monte Carlo-based Shake and Bake algorithm for uniform sampling from the boundary of a convex polytope...

This project develops an approximation algorithm for counting the linear extensions of a partial order by estimating the volume of its associated...

Genome-scale metabolic network reconstructions (GENREs) are comprehensive maps of all known metabolic reactions and associated genes in a given...

The goal of this project is to enhance the Volesti library by implementing a sparse variant of the Billiard Walk sampling algorithm, which proposes...