Monte Carlo and Quasi-Monte Carlo 2024
MCQMC 2024, Waterloo, Canada, August 18–23
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Beschreibung
This volume presents the refereed proceedings of the 16th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held in Waterloo, Ontario, Canada, and organized by the University of Waterloo in August 2024. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems arising, in particular, in finance, statistics, and computer graphics.
This volume presents the refereed proceedings of the 16th International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing that was held in Waterloo, Ontario, Canada, and organized by the University of Waterloo in August 2024. These biennial conferences are major events for Monte Carlo and quasi-Monte Carlo researchers. The proceedings include articles based on invited lectures as well as carefully selected contributed papers on all aspects and applications of Monte Carlo and quasi-Monte Carlo methods. Offering information on the latest developments in these very active areas, this book is an excellent reference resource for theoreticians and practitioners interested in solving high-dimensional computational problems arising, in particular, in finance, statistics, and computer graphics.
Proceedings of the top conference in the field Covers hot topics in the field Top-level contributors
Autor*in
Christiane Lemieux
Themen in »Monte Carlo and Quasi-Monte Carlo 2024«
discrepancy randomized quasi-Monte Carlo rare-event simulation digital nets and lattice rules complexity and tractability of multivariate problems