"Exploring Machine Intelligence", UAL - Creative Computing Institute
Lecturer: Vít Růžička

Class git repo: https://github.com/previtus/cci_exploring_machine_intelligence
Slides: https://github.com/previtus/cci_exploring_machine_intelligence/blob/master/week05_generative-models/ml05_generative-models.pdf

Practicum codes available at: https://github.com/previtus/cci_exploring_machine_intelligence/blob/master/week05_generative-models/ml05_convolutional_VAE.ipynb

--

0:00 - 5:13 Intro
5:13 - 23:26 Generative models: AutoEncoder architecture basics
23:26 - 36:48 AutoEncoder specific interaction, visual attribute vectors
36:48 - 44:18 AutoEncoder uses in artworks
(pause 1)
44:18 - 1:02:38 Generative models: Generative Adversarial Network (GAN) architecture basics
1:02:40 - 1:09:00 Famous GAN architectures from the state-of-the-art research which will work on your custom datasets
1:09:00 - 1:19:40 GANs used in artworks and projects
(pause 2)
1:19:40 - (end) Big Picture, possibilities of artistic curation over Generative models