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Finite Elements and Deep Neural Networks 100

Speaker

Juncai He, Penn State University

Time

2020.03.27 10:00-11:00

Venue

Online—ZOOM APP

Abstract

In this talk, I will first show the connections between ReLU DNNs and linear finite element functions. In addition, I will talk about the approximation properties for ReLU DNNs with a new understanding from the perspective of hierarchical basis. I will then present a constrained linear model that extracts features from images for classifications. Based on such a model, I will finally demonstrate how a new type of CNN, known as MgNet, can be derived by making minor modifications of a classic geometric multigrid method for partial differential equations and then discuss the theoretical and practical potentials of MgNet.

ZOOM Info

Meeting ID: 535 409 777 (no password)