This workshop aims to bring together experts from different communities working on tensor methods and their applications. Tensors and tensor networks are an important object of study in computational many-body physics and chemistry as well as quantum information theory. With the emergence of big data, methods and theory for tensor decomposition have become important in probability, statistics, and machine learning as well. Tensor methods have also received a fair amount of attention from the mathematical community due to their intriguing algebraic and geometric properties, as well as their relationship to computational complexity. This workshop will feature introductory talks from leading experts in all of these fields. The aim of the workshop is to initiate the exchange of ideas between the fields, lead to the beginnings of new interdisciplinary collaborations, and give a good start to the long-term program.
This workshop will include a poster session; a request for posters will be sent to registered participants in advance of the workshop.
(California Institute of Technology)
Ankur Moitra (Massachusetts Institute of Technology)
Elina Robeva (University of British Columbia)
Reinhold Schneider (Technische Universität Berlin, Institut für Mathematik, FG Modellierung, Simulation & Optimieru)
Tao Xiang (Chinese Academy of Sciences)