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ICLR 2024 — Best Papers & Talks (ImageGen, Vision, Transformers, State Space Models) ft. Durk Kingma, Christian Szegedy, Ilya Sutskever

Latent Space: The AI Engineer Podcast

CHAPTER

Understanding Autoencoders and Variational Autoencoders

This chapter covers the essential concepts of deep learning representations through the lens of autoencoders and Variational Auto-Encoders (VAEs). It highlights practical applications such as denoising images and neural inpainting, while also addressing the mathematical principles behind VAEs' unique approach.

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