CREST Japan Science and Technology Agency
Creating information utilization platform by integrating mathematical and information sciences, and development to society Research Supervisor: Naonori Ueda
New developments in statistics for stochastic systems toward data science for large-scale spatiotemporal dependence
Research Director: Nakahiro Yoshida Graduate School of Mathematical Sciences, The University of Tokyo
Outline
By state-of-the-art mathematical sciences, we create a comprehensive system for statistical modeling and statistical analysis of huge dependent data based on the principles of probability theory and mathematical statistics, and promote research in various fields related to time series data. The fusion of data-driven methods such as machine learning with statistical and simulation techniques for stochastic processes built on rigorous mathematics enables exploration and modeling of dependency that traditional time series analysis could not address, for accurate prediction and stochastic control.
This project is closely related to the previous JST CREST project, Mathematical statistics and stochastic analysis for modeling and analysis of complex random systems (2014 Oct - 2021 Sep).
This project provides partial support for the following seminar series.Statistics and Probability Seminar / APSPS and BayesComp Seminar
