Deep Learning Course (NYU, Spring 2020) - Week 9 – Practicum: (Energy-based) Generative adversarial networks

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42.5 hours of video
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Summary

Keywords

Deep Learning Yann LeCun generative variational autoencoder PyTorch GAN generative adversarial network energy model EBGAN generator discriminator cost

Full Transcript

Course website: http://bit.ly/DLSP20-web Playlist: http://bit.ly/pDL-YouTube Speaker: Alfredo Canziani Week 9: http://bit.ly/DLSP20-09 0:00:00 – Week 9 – Practicum PRACTICUM: http://bit.ly/DLSP20-09-3 During this week’s practicum, we explored Generative Adversarial Networks (GANs) and how they can produce realistic generative models. We then compared GANs with VAEs from week 8 to highlight key differences between two networks. Next, we discussed several model limitations of GANs. Finally, we looked at the source code for the PyTorch example Deep Convolutional Generative Adversarial Networks (DCGAN). 0:00:57 – Intro to GANs 0:30:44 – Difference between GANs and VAEs and major pitfalls in GANs 0:48:31 – DCGAN source code

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