https://github.com/machine-learning-tokyo/generative_deep_learning

Generative Deep Learning Sessions led by Anugraha Sinha (Machine Learning Tokyo)
https://github.com/machine-learning-tokyo/generative_deep_learning

gans generative-adversarial-networks generative-model stylegan vae wgan wgan-gp

Last synced: 6 months ago
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Generative Deep Learning Sessions led by Anugraha Sinha (Machine Learning Tokyo)

• Host: GitHub
• URL: https://github.com/machine-learning-tokyo/generative_deep_learning
• Owner: Machine-Learning-Tokyo
• License: mit
• Created: 2020-03-21T15:36:00.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2020-05-09T14:22:12.000Z (over 5 years ago)
• Last Synced: 2025-04-18T16:26:34.212Z (6 months ago)
• Topics: gans, generative-adversarial-networks, generative-model, stylegan, vae, wgan, wgan-gp
• Language: Jupyter Notebook
• Homepage: https://www.meetup.com/Machine-Learning-Tokyo/
• Size: 4.17 MB
• Stars: 24
• Watchers: 4
• Forks: 9
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Generative Deep Learning

This repository contains notes from the MLT Generative Deep Learning sessions (reading & discussion), led by Anuragah Sinha.

# Sessions

All sessions are dedicated to reading and discussing:

["Generative Deep Learning" by David Foster (O'Reilly)](https://www.oreilly.com/library/view/generative-deep-learning/9781492041931/)

Notes including images and other references:

- Title: Generative Deep Learning

- Author: David Foster

- Release date: June 2019

- Publisher(s): O'Reilly Media, Inc.

- ISBN: 9781492041931

## Part 1 - Introduction to Generative Deep Learning

📌 Session # 1

Chapter 1 : Generative Modeling

Chapter 2 : Deep Learning

📌 Session #2

Chapter 3 : Variational Autoencoders

📌 Session #3

Chapter 4 : Generative Adversarial Networks

## Part 2 - Teaching Machines to Paint, Write, Compose and Play

📌 Session #4

Chapter 5 : Paint

📌 Session #5

Chapter 6 : Write

📌 Session #6

Chapter 7 : Compose

📌 Session #7

Chapter 8 : Play

📌 Session #8

Chapter 9 : The Future of Generative Modelling

Conclusion

Sessions are ongoing and held online weekly on Saturdays 3-5 pm (JST). Join us on [Meetup](https://www.meetup.com/Machine-Learning-Tokyo/).