Uploaded June 2021 | Updated September 2026, 1 week ago
❤️ Become The AI Epiphany Patreon ❤️ ► patreon.com/theaiepiphany
In this video I cover VQ-VAEs papers:
1) Neural Discrete Representation Learning
2) Generating Diverse High-Fidelity Images with VQ-VAE-2 (the only difference is the existence of a hierarchical structure of latents and priors)
Many novel interesting AI papers such as DALL-E and Jukebox from OpenAI as well as VQ-GAN build off of VQ-VAEs, so it's fairly important to have a good grasp of how they work.
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✅ VQ-VAE1 paper: arxiv.org/abs/1711.00937
✅ VQ-VAE2 paper: arxiv.org/abs/1906.00446
✅ PyTorch code: colab.research.google.com/github/zalandoresearch/pytorch-vq-vae/blob/master/vq-vae.ipynb
✅ ELBO explained: mbernste.github.io/posts/elbo
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⌚️ Timetable:
00:00 Intro
01:10 A tangent on autoencoders and VAEs
07:50 Motivation behind discrete representations
08:25 High-level explanation of VQ-VAE framework
11:20 Diving deeper
13:05 VQ-VAE loss
16:20 PyTorch implementation
23:30 KL term missing
25:50 Prior autoregressive models
28:50 Results
32:20 VQ-VAE two
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
💰 BECOME A PATREON OF THE AI EPIPHANY ❤️
If these videos, GitHub projects, and blogs help you,
consider helping me out by supporting me on Patreon!
The AI Epiphany ► patreon.com/theaiepiphany
One-time donation:
paypal.com/paypalme/theaiepiphany
Much love! ❤️
Huge thank you to these AI Epiphany patreons:
Eli Mahler
Petar Veličković
Zvonimir Sabljic
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
💡 The AI Epiphany is a channel dedicated to simplifying the field of AI using creative visualizations and in general, a stronger focus on geometrical and visual intuition, rather than the algebraic and numerical "intuition".
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
👋 CONNECT WITH ME ON SOCIAL
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GitHub ► github.com/gordicaleksa
📚 FOLLOW ME ON MEDIUM:
Medium ► gordicaleksa.medium.com
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#vqvae #discretelatents #generativemodeling
❤️ Become The AI Epiphany Patreon ❤️ ► patreon.com/theaiepiphany
In this video I cover VQ-VAEs papers:
1) Neural Discrete Representation Learning
2) Generating Diverse High-Fidelity Images with VQ-VAE-2 (the only difference is the existence of a hierarchical structure of latents and priors)
Many novel interesting AI papers such as DALL-E and Jukebox from OpenAI as well as VQ-GAN build off of VQ-VAEs, so it's fairly important to have a good grasp of how they work.
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
✅ VQ-VAE1 paper: arxiv.org/abs/1711.00937
✅ VQ-VAE2 paper: arxiv.org/abs/1906.00446
✅ PyTorch code: colab.research.google.com/github/zalandoresearch/pytorch-vq-vae/blob/master/vq-vae.ipynb
✅ ELBO explained: mbernste.github.io/posts/elbo
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
⌚️ Timetable:
00:00 Intro
01:10 A tangent on autoencoders and VAEs
07:50 Motivation behind discrete representations
08:25 High-level explanation of VQ-VAE framework
11:20 Diving deeper
13:05 VQ-VAE loss
16:20 PyTorch implementation
23:30 KL term missing
25:50 Prior autoregressive models
28:50 Results
32:20 VQ-VAE two
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
💰 BECOME A PATREON OF THE AI EPIPHANY ❤️
If these videos, GitHub projects, and blogs help you,
consider helping me out by supporting me on Patreon!
The AI Epiphany ► patreon.com/theaiepiphany
One-time donation:
paypal.com/paypalme/theaiepiphany
Much love! ❤️
Huge thank you to these AI Epiphany patreons:
Eli Mahler
Petar Veličković
Zvonimir Sabljic
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
💡 The AI Epiphany is a channel dedicated to simplifying the field of AI using creative visualizations and in general, a stronger focus on geometrical and visual intuition, rather than the algebraic and numerical "intuition".
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
👋 CONNECT WITH ME ON SOCIAL
LinkedIn ► linkedin.com/in/aleksagordic
Twitter ► twitter.com/gordic_aleksa
Instagram ► instagram.com/aiepiphany
Facebook ► facebook.com/aiepiphany
👨👩👧👦 JOIN OUR DISCORD COMMUNITY:
Discord ► discord.gg/peBrCpheKE
📢 SUBSCRIBE TO MY MONTHLY AI NEWSLETTER:
Substack ► aiepiphany.substack.com
💻 FOLLOW ME ON GITHUB FOR COOL PROJECTS:
GitHub ► github.com/gordicaleksa
📚 FOLLOW ME ON MEDIUM:
Medium ► gordicaleksa.medium.com
▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬
#vqvae #discretelatents #generativemodeling
