第98回研究会

開催日：

2025年5月2日(金) 16:00-17:00

会場：

丸の内永楽ビルディング18階 東京都立大学 丸の内サテライトキャンパス
(Zoomでも同時配信します)

報告者：

Marius Hofert 氏（Associate Professor of Statistics, The University of Hong Kong）

タイトル：

Dependence modeling with neural networks: Random number generation and model assessment

概要Overview

Generative moment matching networks (GMMNs) are introduced as dependence models with two particularly important applications in mind. First, for generating approximate quasi-random samples from multivariate models with any underlying copula in order to compute estimates under variance reduction. Once trained on pseudo-random samples from a parametric model or on real data, GMMNs only require a multivariate standard uniform randomized QMC point set as input and are thus fast in estimating expectations of interest under dependence with variance reduction. Second, GMMNs can learn maps from d-dimensional samples with any underlying dependence structure to multivariate uniformity in d’ dimensions, which can be used for dependence model assessment and selection. Besides a numerical assessment, particularly of interest is the case d’ = 2, which allows for a graphical assessment and selection approach. A distinct feature of this approach is to allow one to identify regions of the domain in which a candidate model does not provide an adequate fit.

講師ご略歴Profile for speakers

Marius Hofert is an Associate Professor in the Department of Statistics and Actuarial Science and the Director of the Master of Data Science programme of the School of Computing and Data Science at The University of Hong Kong. He obtained his PhD in mathematics from Ulm University in 2010. He then held a postdoctoral research position at RiskLab, ETH-Zurich. Afterwards, he was Guest Professor in the Department of Mathematics at the Technische Universität München, Visiting Assistant Professor in the Department of Applied Mathematics at the University of Washington, Seattle, and Associate Professor in the Department of Statistics and Actuarial Science at University of Waterloo. Marius’ research interests are dependence modeling, computational statistics, data science and quantitative risk management. He has offered several courses, mini-courses, workshops, summer or winter schools in these areas, including courses on risk management at the Risk Management Institute at National University of Singapore and at the 29th International Summer School of the Swiss Association of Actuaries. Marius has also participated in the education of actuaries and risk managers by developing teaching material and software freely available on qrmtutorial.org.

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