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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

Advancements in Variational Autoencoders

This chapter explores the evolution and significance of Variational Autoencoders (VAEs), emphasizing their foundational techniques and collaborative research efforts recognized at the ICLR conference. It highlights the historical development of VAEs, challenges in optimization, and their applications across various fields, including healthcare and video compression. Additionally, the chapter discusses the relationship between VAEs and diffusion models, showcasing their impact on generative modeling.

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