A two-day summit of talks, activities, and workshops
A two-day summit of talks, activities, and workshops
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To contribute a talk or to receive the zoom information of this workshop, please register for this workshop.
Day 1
Day 1
Day 1 focuses on the approximation and generalization theory of deep neural networks. You will understand why deep neural networks are powerful and how powerful they would be (i.e., the limitation), especially for learning high-dimensional functions! You will understand how to interpret deep learning instead of treating it as a black-box!
Day 2
Day 2
Day 2 focuses on the optimization theory and algorithms of deep learning with applications to various mathematical problems in science and engineering. You will understand why deep learning works so well with simple optimization algorithms for various data sets! You will understand how to apply deep learning in mathematical problems through the exciting examples in our invited talks!
The goal of this event is to stimulate collaborative efforts to advance scientific machine learning and its theoretical foundation.
The goal of this event is to stimulate collaborative efforts to advance scientific machine learning and its theoretical foundation.
What starts here may change your understanding of deep learning. Present, discuss, and collaborate!
Invited Speakers
Invited Speakers
California Institute of Technology
Sandia National Laboratories
Texas A&M University
Columbia University
Brown University
University of Chicago
Ludwig Maximilian University of Munich
Princeton University
Duke University
Stanford University
University of California, Los Angeles
National University of Singapore
Columbia University
Pennsylvania State University
Stanford University
University of California, Berkeley
The Venue
The Venue
Zoom link to be announced on August 10, 2021
Zoom link to be announced on August 10, 2021
Let us know if you'll be attending!
Let us know if you'll be attending!
This workshop is jointly supported by Institute for Mathematics and its Applications and the Department of Mathematics at Purdue University
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