The biennial International Conference on Monte Carlo Methods and Applications (MCM) is a mathematically-oriented meeting devoted to the study of stochastic simulation and Monte Carlo methods in general, from the theoretical viewpoint and in terms of their effective applications in different areas such as finance, statistics, machine learning, computer graphics, computational physics, biology, chemistry, and scientific computing in general. It is one of the most prominent conference series devoted to research on the mathematical aspects of stochastic simulation and Monte Carlo methods.
Conference topics include:
Monte Carlo methods and principles; pseudorandom number generators; low-discrepancy point sets and sequences in various spaces; quasi-Monte Carlo and randomized quasi-Monte Carlo methods; simulation of random variates and random processes; variance reduction and efficiency improvement methods for simulation; rare-event simulation methods; multilevel Monte Carlo methods; stochastic optimization methods based on simulation and random search; simulation algorithms for highly-parallel computing environments; tractability and complexity analysis of multivariate problems (integration, approximation, etc.); Monte Carlo and quasi-Monte Carlo methods for stochastic differential equations and partial differential equations; Markov chain Monte Carlo particle filters, splitting, and other adaptive learning methods; Monte Carlo methods in machine learning; applications in physics, chemistry, biology, economy, finance, statistics, management, medical science, computer graphics, etc.