Stochastic computing and structure preserving methods
 Organizer(s):
Name:
Affiliation:
Country:
Yanzhao Cao
Auburn University
USA
Chuchu Chen
Academy of Mathematics and Systems Science, Chinese Academy of Sciences
Peoples Rep of China
Jialin Hong
Academy of Mathematics and Systems Science, Chinese Academy of Sciences
Peoples Rep of China
 Introduction:  
  Stochastic computing has developed extensive and profound interactions with various branches of mathematics and with disciplines beyond mathematics, leading to the emergence of novel methodologies and research directions. This session is devoted to numerical methods and simulations for stochastic (partial) differential equations, with topics including, but not limited to, the construction and analysis of stochastic structure-preserving algorithms, stochastic ergodic methods, and related machine learning algorithms. The session seeks to provide a platform for the presentation of recent advances and the exchange of new ideas.