Mathematical Advances in Deep Learning - Part II of II | SIAM

Content
2019 SIAM Conference on Com...
Mathematical Advances in De...

Mathematical Advances in Deep Learning - Part II of II

Presentation Icon

CSE19 - MS35-1: A Mean-field Optimal Control Formulation of Deep Learning

Presentation: Jiequn Han, Princeton University, U.S., 21 min 8 sec

CSE19 - MS35-1: A Mean-field Optimal Control Formulation of Deep Learning

Document: CSE19 - MS35-1: A Mean-field Optimal Control Formulation of Deep Learning

Presentation Icon

CSE19 - MS35-2: Semi-Implicit Convolutional Neural Networks

Presentation: Keegan Lensink, University of British Columbia, Canada, 19 min 39 sec

CSE19 - MS35-2: Semi-Implicit Convolutional Neural Networks

Document: CSE19 - MS35-2: Semi-Implicit Convolutional Neural Networks

Presentation Icon

CSE19 - MS35-3: Trimming Linear and non-Linear Models

Presentation: Aleksandr Aravkin, 20 min 31 sec

CSE19 - MS35-3: Trimming Linear and non-Linear Models

Document: CSE19 - MS35-3: Trimming Linear and non-Linear Models

Presentation Icon

CSE19 - MS35-4: Deep Inversion - Latent Space Analysis of Autoencoders for Inverse Problems

Presentation: Christoph Brune, University of Twente, Netherlands, 21 min 18 sec

CSE19 - MS35-4: Deep Inversion - Latent Space Analysis of Autoencoders for Inverse Problems

Document: CSE19 - MS35-4: Deep Inversion - Latent Space Analysis of Autoencoders for Inverse Problems