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Fixed chapter order
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udlbook
2022-12-15 11:02:48 +00:00
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@@ -29,9 +29,9 @@ To be published by MIT Press.
<li> Chapter 12 - Transformers <li> Chapter 12 - Transformers
<li> Chapter 13 - Graph neural networks <li> Chapter 13 - Graph neural networks
<li> Chapter 14 - Unsupervised learning <li> Chapter 14 - Unsupervised learning
<li> Chapter 15 - Variational auto-encoders <li> Chapter 15 - Generative adversarial networks
<li> Chapter 16 - Normalizing flows <li> Chapter 16 - Normalizing flows
<li> Chapter 17 - Generative adversarial networks <li> Chapter 17 - Variational auto-encoders
<li> Chapter 18 - Diffusion models <li> Chapter 18 - Diffusion models
<li> Chapter 19 - Deep reinforcement learning <li> Chapter 19 - Deep reinforcement learning
<li> Chapter 20 - Why does deep learning work? <li> Chapter 20 - Why does deep learning work?
@@ -65,9 +65,9 @@ Citation:
<li> Chapter 12 - Transformers: Slides / Notebooks / <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap12PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap12.pptx">PowerPoint Figures</a> <li> Chapter 12 - Transformers: Slides / Notebooks / <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap12PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap12.pptx">PowerPoint Figures</a>
<li> Chapter 13 - Graph neural networks: Slides / Notebooks / <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap13PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap13.pptx">PowerPoint Figures</a> <li> Chapter 13 - Graph neural networks: Slides / Notebooks / <a href="https://github.com/udlbook/udlbook/raw/main/PDFFigures/UDLChap13PDF.zip">PDF Figures</a> / <a href="https://github.com/udlbook/udlbook/raw/main/Slides/UDLChap13.pptx">PowerPoint Figures</a>
<li> Chapter 14 - Unsupervised learning: Slides / Notebooks / PDF Figures / Powerpoint Figures <li> Chapter 14 - Unsupervised learning: Slides / Notebooks / PDF Figures / Powerpoint Figures
<li> Chapter 15 - Variational auto-encoders: Slides / Notebooks / PDF Figures / PowerPoint Figures <li> Chapter 15 - Generative adversarial networks: Slides / Notebooks / PDF Figures / PowerPoint Figures
<li> Chapter 16 - Normalizing flows: Slides / Notebooks / PDF Figures / PowerPoint Figures <li> Chapter 16 - Normalizing flows: Slides / Notebooks / PDF Figures / PowerPoint Figures
<li> Chapter 17 - Generative adversarial networks: Slides / Notebooks / PDF Figures / PowerPoint Figures <li> Chapter 17 - Variational auto-encoders: Slides / Notebooks / PDF Figures / PowerPoint Figures
<li> Chapter 18 - Diffusion models: Slides / Notebooks / PDF Figures / PowerPoint Figures <li> Chapter 18 - Diffusion models: Slides / Notebooks / PDF Figures / PowerPoint Figures
<li> Chapter 19 - Deep reinforcement learning: Slides / Notebooks / PDF Figures / PowerPoint Figures <li> Chapter 19 - Deep reinforcement learning: Slides / Notebooks / PDF Figures / PowerPoint Figures
<li> Chapter 20 - Why does deep learning work?: Slides / Notebooks / PDF Figures / PowerPoint Figures <li> Chapter 20 - Why does deep learning work?: Slides / Notebooks / PDF Figures / PowerPoint Figures