The main development is currently performed in volesti, a generic open source C++ library, with R and Python interfaces. volesti implements various algorithms for high-dimensional sampling and volume approximation as well as functions for copula estimation in financial modelling and metabolic network analysis.
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Who is using our software ?
A. Venzke, D.K. Molzahn, S. Chatzivasileiadis - Efficient creation of datasets for data-driven power system applications, Electric Power Systems Research, Volume 190, 2021. WWW
P.Z.D. Martires, Samuel Kolb - Monte Carlo Anti-Differentiation for Approximate Weighted Model Integration, 2020. WWW
C. Maria, O. Rouillé - Computation of Large Asymptotics of 3-Manifold Quantum Invariants, 2020. WWW
Google Summer of Code
GeomScale was accepted and participated in Google Summer of Code 2020 as a mentoring organization. The following projects was succesfully completed:
- A comparative study of uniform high dimensional samplers.
- Optimization and Sum of Squares.
- Sampling from High-Dimensional log-concave densities.
Members of GeomScale has succesfully participated in GSoC in the past with the R-project for statistical computing.