About Fangyuan Yu Fangyuan Yu Ph.D. Student, Statistics computational probability Monte Carlo Methodology Fangyuan Yu is a Ph.D. student in the Statistics program at KAUST, his supervisor is Professor Ajay Jasra. Education and Early Career Fangyuan holds a master's degree in statistics from the National University of Singapore (NUS). He also holds a master's degree and a bachelor's degree in mathematics and applied mathematics at Shandong University, China. Before joining KAUST, Fangyuan worked as a research assistant in the Department of Statistics and Applied Probability, National University of Singapore from August 2018 to July 2019. His principal investigator was Professor Ajay Jasra. Research Events Presented Events Mar 6 - Mar 12, 2022 Coupled Sampling Methods for Filtering Fangyuan Yu, Ph.D. Student, Statistics Mar 7, 15:00 - 17:00 KAUST Monte carlo methods computational statistics Markov models This thesis focuses on the use of multilevel Monte Carlo methods to achieve optimal error versus cost performance for statistical computations in hidden Markov models as well as for unbiased estimation under four cases: nonlinear filtering, unbiased filtering, unbiased estimation of hessian, continuous linear Gaussian filtering.
Coupled Sampling Methods for Filtering Fangyuan Yu, Ph.D. Student, Statistics Mar 7, 15:00 - 17:00 KAUST Monte carlo methods computational statistics Markov models This thesis focuses on the use of multilevel Monte Carlo methods to achieve optimal error versus cost performance for statistical computations in hidden Markov models as well as for unbiased estimation under four cases: nonlinear filtering, unbiased filtering, unbiased estimation of hessian, continuous linear Gaussian filtering.
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