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Generative Adversarial Networks (GANs)

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13 April 2017


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Generative Adversarial Networks (GANs)

Abstract

Ian Goodfellow, Research Scientist at OpenAI takes us through Generative Adversarial Networks at AI0 With The Best online developer conference September 2016 #AIWTB.

Followed by a super Q&A session

Q&A

  • 28:40 Can you explain the problem about GANs not knowing how to place body parts and textures within the image net - what are some solutions to those problems?
  • 30:45 Specifically how can you place body parts and place 3D texture?
  • 31:30 What are the commercial applications of GANs?
  • 33:04 Where do you see GANs being applied outside of image related tasks?
  • 33:13 How can you generate feedback loops in a GAN so it generates an output similar to the input in its dimensions to predict the next step in a time series ie. a video sequence like in the case of WaveNet?
  • 33:34 What do you predict it will take to get the output to scale to a much larger output dimension?
  • 34:16 Can GANs be used for Data Compression?
  • 35:20 What is your goal with GANs?

NIPS 2016 Workshop on Adversarial Training

Introduction to GANs


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