A Benchmarking Framework for Geometric Random Walks
Contributor: Chrthegreat
Sampling from high-dimensional convex polytopes is a fundamental problem with applications in statistics, machine learning, optimization, and systems...
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GeomScale
Scalable geometric and statistical software
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Topics
computational biologycomputational geometrydatamathematicsstatistics
- Total projects
- 34
- Years participating
- 7
- Most recent
- 2026
Participation history
Historical projects
Dynamic Volume Updating of Convex Polytopes via Random-Walk Sampling
Contributor: Iva Janković
This project explores the problem of estimating how the volume of a high-dimensional convex polytope changes under sequential constraint additions....
Benchmark Polytope Import Suite For Volesti
Contributor: JimmysPavlou
This project aims to develop a Benchmark Polytope Import Suite for the volesti library, enabling automated conversion of standard Linear Programming...
Counting linear extensions with volume computation and applications in AI
Contributor: Ke Shih
This project will implement a new volume-based approach for approximately counting linear extensions of partially ordered sets in volesti. The core...
Expose C++ Sampling, Rounding and Volume Computation in Dingo
Contributor: Akis Schinas
Dingo is a Python library built on top of the C++ library volesti, primarily designed for sampling from convex polytopes, especially within the...
Randomized SDP solver and improved preprocessing
Contributor: Angelos Korakitis
The proposed project aims to continue the implementation of the semidefinite pro- gramming (SDP) solver in the VolEsti library and to integrate it...
Shake and Bake - Sampling from the boundary of convex polytopes
Contributor: Iva Janković
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...
Counting Linear Extensions with Volume Computation and Applications in AI
Contributor: Sophia Qian
This project develops an approximation algorithm for counting the linear extensions of a partial order by estimating the volume of its associated...
Initiating the dingo-stats library
Contributor: Sotirios Touliopoulos
Genome-scale metabolic network reconstructions (GENREs) are comprehensive maps of all known metabolic reactions and associated genes in a given...
Sparse Polytope Sampling via Lazy Rounding
Contributor: Vladimir Necula
The goal of this project is to enhance the Volesti library by implementing a sparse variant of the Billiard Walk sampling algorithm, which proposes...
Machine Learning and Optimization for Finance: Index Replication
Contributor: Ho Thi Minh Ha
Indexes are baskets of stocks with specific characteristic. They provide examples for diversification in investing to mitigate the volatility of...
Pre- and post-sampling features to leverage flux sampling at both the strain and the community level
Contributor: Sotiris Touliopoulos
The first genome-scale models of metabolism appeared in 1999 and 2000. In the following years fundamental Microbial Systems concepts were developed...
Develop a new rounding method for convex polytopes
Contributor: Luca Perju
The goal of this project is to improve currently existing implementations for rounding convex polytopes from Volesti as well as develop a new method...
Efficient Volume Computation
Contributor: Vladimir Necula
The current state-of-the-art algorithms for the volume computation of high dimensional convex bodies, such as the one currently used within the...
Refactor Multiphase Monte Carlo Sampling for volesti and dingo
Contributor: Akis Schinas
The proposed project aims to refactor the Multiphase Monte Carlo Sampling (MMCS) algorithm, currently implemented in Python with Cython bindings, to...
Modernize Linear Program solver interface in dingo
Contributor: Ke Shih
The proposed project aims to modernize the Linear Program (LP) solver interface in dingo, a Python package for analyzing metabolic net- works. By...
Improving sampling routines for correlation matrices and R interface
Contributor: Atrayee Samanta
The goal of this project is to (1) improve sampling routines for correlation matrices and (2) further enhance the R interface with sampling...
Support exponential sampling from the space of steady states of a metabolic network
Contributor: Guillermo Martin
My proposal is to extend the Python package dingo with two Markov Chain Monte Carlo sampling methods, which will enable exponential sampling from the...
Memory allocation in facet redundancy removal in dingo
Contributor: Nitish Malang
This project will improve the memory allocation in the main routine for facet redundancy removal in GeomScale's Python package dingo. The project is...
Move R Interface of Volesti to a New Repository
Contributor: Soumya Tarafder
The main goal of this project is to create a dedicated repository for the R interface code of Volesti, a tool developed by GeomScale for volume...
Automatic differentiation support in volesti
Contributor: Zhang Zhuyan
The most efficient algorithm to sample from a log-concave distribution, that volesti supports is the Hamiltonian Monte Carlo with leapfrog...
Counting linear extensions with volume computation
Contributor: reyan_ahmed
In this project, we will implement different algorithms to count linear extensions approximately. In the problem of counting the linear extensions,...
Memory allocation in facet redundancy removal in dingo
Contributor: Haris Zafeiropoulos
Sampling and volume computation of convex polytopes is a challenging computational problem with many applications in inference from linear...
Support for new sampling methods and new model formats in dingo
Contributor: KONSTANTINOS PALLIKARIS
Package dingo is a python package that analyzes metabolic networks. It relies on high dimensional sampling with Markov Chain Monte Carlo (MCMC)...
Randomized SDP solver with Riemannian Hamiltonian Monte Carlo
Contributor: Ioannis Iakovidis
The relationship between sampling and optimization has gained increasing interest in recent years. A great number of optimization algorithms that are...
Sampling correlation matrices
Contributor: Huu Phuoc Le
We study the sampling of correlation matrices from a given probability density, which has applications in various scientific, engineering and...
High dimensional geometric computations with least matrix inequalities
Contributor: Alexandros Manochis
Package volesti supports volume estimation for polytopes, providing several randomized approximation methods. The most efficient implementation...
From DNA sequences to metabolic interactions: building a pipeline to extract key metabolic processes
Contributor: Haris Zafeiropoulos
Metabolic modeling has been interwoven with constraing-based methods. The value of randomized sampling in the framework of metabolic modeling has...
Parallel Geometric Random Walks with Sparse Numerical Optimizations
Contributor: Konstantinos Pallikaris
Package volesti provides several geometric random walks for high dimensional sampling from convex polytopes. The current implementations can be used...
GeomScale: Monte Carlo Integration
Contributor: Suraj Choubey
Integration is a fundamental problem in mathematics, physics and computer science with many applications that span the whole spectrum of sciences and...
Counting linear extensions
Contributor: Vaibhav Thakkar
The problem of counting the linear extensions of a given partial order consists of finding (counting) all the possible ways that we can extend the...
Optimization and Sum of Squares
Contributor: Bento Natura
We aim to provide an implementation of modern approaches to Sum of Squares problems.
A comparative study of uniform high dimensional samplers
Contributor: Alexandros Manochis
Uniform sampling from convex polytopes in high dimensions is very useful in many scientific fields and applications. The package volesti is a C++...
Sampling from High-Dimensional log-concave densities
Contributor: Marios Papachristou
This proposal aims to provide functionality on sampling from high-dimensional densities. A log-concave density is a density g(x) proportional to...