MDS20 Minitutorial: Solving Inverse Problems with Deep Learning by Lexing Ying

/ May 19, 2020/

Abstract: This talk is about some recent progress on solving inverse problems using deep learning. Compared to traditional machine learning problems, inverse problems are often limited by the size of the training data set. We show how to overcome this issue by incorporating mathematical analysis and physics into the design of neural network architectures.

Lexing Ying, Stanford University, U.S., [email protected]

This is one of six minitutorial talks organized by Carola-Bibiane Schönlieb (University of Cambridge, United Kingdom) and Ozan Öktem (KTH Stockholm, Sweden) under the title “Deep Learning for Inverse Problems and Partial Differential Equations” as part of the 2020 SIAM Conference on Mathematics of Data Science. For more information, visit https://meetings.siam.org/sess/dsp_programsess.cfm?SESSIONCODE=69622.