会议信息
报告题目
Martingale Benamou-Brenier
报告嘉宾
Mathias Beiglböck
(Universität Wien, Austria)
报告时间
2024年11月15日20:30(北京时间)
直播间链接
https://live.bilibili.com/h5/21963219
报告嘉宾
Mathias Beiglböck is professor at the University of Vienna(Austria) since 2018.From 2015 to 2018 he held a professorship at Vienna University of Technology.He studied mathematics at Vienna University of Technology,where he obtained his PhD degree in 2004 under the supervision of Reinhard Winkler,and completed his habilitation at the University of Vienna in 2010.As post doctoral researcher he worked with Walter Schachermayer,at MSRI(Berkeley),and at the University of Bonn.
Mathias Beiglböck's research is in probability theory with an emphasis on stochastic process theory,including theoretical results on martingale theory,optimal transport problems,and applications to Stochastic Finance.
Mathias Beiglböck received several prizes,for example the START-Prize of the Austrian Science Fund in 2014,and he lead several research projects.
报告摘要
In classical optimal transport, the contributions of Benamou−Brenier and McCann regarding the time-dependent version of the problem are cornerstones of the field and form the basis for a variety of applications in other mathematical areas. Stretched Brownian motion provides an analogue for the martingale version of this problem. We provide a characterization in terms of gradients of convex functions,similar to the characterization of optimizers in the classical transport problem for quadratic distance cost.This is based on joint work with Julio Backhoff-Veraguas, Walter Schachermayer and Bertram Tschiderer.
讲座海报
期刊简介
Probability, Uncertainty and Quantitative Risk 主要发表现代概率论的重大创新性成果,内容包括随机分析和统计、随机过程、动态分析和控制理论及其在金融学、经济学、生物学、计算机科学等领域的应用。期刊目前已被ESCI、Scopus、Mathematical Reviews、zbMATH Open等数据库收录,2024年影响因子IF=1.0,在“STATISTICS & PROBABILITY”学科分类中位于Q3区。在中科院分类中位于大类数学2区、小类统计学与概率论2区,入选《数学领域高质量科技期刊分级目录》T2区。
期刊网站:https://www.aimsciences.org/PUQR
投稿网址:https://ef.msp.org/submit_new.php?j=puqr
邮箱:probability-risk@sdu.edu.cn
电话:0531-88366741
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