Special thanks to Pieterjan Robbe for his new demo on Elliptic PDEs and continued collaboration on multilevel (Quasi-) Monte Carlo! The Jupyter notebook version of this demo is available in the QMCPy GitHub.
Hope to see you virtually at Monte Carlo Methods 2021, in August 2021. This the prime odd year Monte Carlo conference featuring computer scientists, mathematicians, and statisticians. We are organizing a special session on Quasi-Monte Carlo software. More info coming soon.
We recently uploaded an article on Quasi-Monte Carlo Software to https://arxiv.org/abs/2102.07833. Abstract: Practitioners wishing to experience the efficiency gains from using low discrepancy sequences need correct, well-written software. This article, based on our MCQMC 2020 tutorial, describes some of the better quasi-Monte Carlo (QMC) software available. We highlight the key software components required to approximateContinue reading “Quasi-Monte Carlo Software Article”
The developers of QMCPy are happy to announce the release of version 1.0 on February 12, 2021, Chinese New Year! We would like to thank all those who have made this development possible. A special thank you to Developers: Sou-Cheng T. Choi, Fred J. Hickernell, Michael McCourt, Jagadeeswaran Rathinavel, and Aleksei Sorokin; Collaborators: Mike Giles,Continue reading “QMCPy Version 1.0”