L17.6 A Variational Autoencoder for Face Images in PyTorch   Code Example @SebastianRaschka
L17.6 A Variational Autoencoder for Face Images in PyTorch   Code Example  @SebastianRaschka
Uploaded April 2021 | Updated September 2026, 2 weeks ago
Sebastian's books: sebastianraschka.com/books

Slides: sebastianraschka.com/pdf/lecture-notes/stat453ss21/L17_vae__slides.pdf

L17 code: github.com/rasbt/stat453-deep-learning-ss21/tree/main/L17

Discussing 2_VAE_celeba-sigmoid_mse.ipynb,
3_VAE_nearest-neighbor-upsampling.ipynb 
& 4_VAE_celeba-inspect-latent.ipynb

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L17.6 A Variational Autoencoder for Face Images in PyTorch   Code ExampleL12.2 Learning Rate Schedulers in PyTorchL5.4 (Optional) Calculus Refresher I: DerivativesL19.2.2 Implementing a Character RNN in PyTorch  Code ExampleHow Claudes Text Watermarking WorksDesigning Generative Adversarial Networks for Privacy-enhanced Face Recognition (Conference rec.)L2.3 The Origins of Deep LearningL19.5.1 The Transformer ArchitectureL11.4 Why BatchNorm WorksL10.4 L2 Regularization for Neural NetsL13.9.2 Saving and Loading Models in PyTorchReinforcement Learning with Human Feedback (RLHF) in 4 minutes
Sebastian Raschka |

L17.6 A Variational Autoencoder for Face Images in PyTorch -- Code Example

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