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GPUniversity of Deep Learning and Beyond

January 24, 2018 - 10:00am
Huang Engineering Center, Mackenzie Room (Huang 300)

-- Registration for this event is FULL --

Every year, ICME and NVIDIA present GPUniversity of Deep Learning and Beyond. 

At this event, participants will explore the future of AI computing, hear from Stanford faculty who are leveraging GPU computing in their research and participate in demos and deep learning workshops with experts who are creating new realities with AI.

When: Wednesday, January 24, 2018
Time: 10:30AM - 4:30PM
Where: Mackenzie Room (3rd Floor), Jen-Hsun Huang Engineering Building, Stanford University
Who it's for: All Stanford University, Undergraduate, Graduate Students, Postdocs, Researchers, Professors and Faculty


SCHEDULE OF EVENTS

10:00AM - 10:25AM: Registration & Breakfast
 
10:25AM - 10:30AM: Welcome/Intro by Margot Gerritsen
 
10:30AM – 11:30AM: Keynote - Bill Dally, Chief Scientist at NVIDIA, Senior Vice President of NVIDIA Research and Stanford Professor
 
11:30AM – 12:30PM Technical Talks
  • Silvio Savarese, Associate Professor of Computer Science and Director of SAIL at Stanford University
  • Eric Darve, Associate Professor of Mechanical Engineering at Stanford University
  • Jenny Suckale, Assistant Professor of Geophysics at Stanford University
  • Amir Saadat, Postdoctoral Scholar of Chemical Engineering at Stanford University
12:30PM – 2:30PM: Lunch and Demos (in the Huang Basement Level)
 
2:30PM - 4:30PM: Deep Learning Institute Workshop, Image Creation using Generative Adversarial Networks with TensorFlow and DIGITS (in Huang 300)

ABOUT THE DEEP LEARNING WORKSHOP

Topic: Image Creation using Generative Adversarial Networks (GAN) with TensorFlow and DIGITS
Instructor: Jonathan Bentz
 
This Lab will guide you through the process of training a Generative Adversarial Network (GAN) to generate image contents in DIGITS. You will learn how to: 
  • Use Generative Adversarial Networks (GANs) to create handwritten numbers
  • Visualize the feature space and use attribute vector to generate image analogies
  • Train a GAN to generate images with set attributes
Upon completion of this Section, you will be able to use GANs to generate images by manipulating feature space.
 
Important Note: Each workshop participant must bring their own laptop to the event in order to run the DLI Lab. A current browser is needed. For optimal performance, Chrome, Firefox or Safari for Macs are recommended. IE is operational but does not provide the best performance.