mlsanityData to 14 Oct 2026

An Introduction to Variational Autoencoders

arXiv 1906.02691 ↗First posted 6 Jun 2019cs.LG stat.MLcited by 1,000

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Cited by 146 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Variational autoencoders provide a principled framework for learning deep latent-variable models and corresponding inference models. In this work, we provide an introduction to variational autoencoders and some important extensions.

Key facts. Cited by 1,000 papers in the map (data through 14 Oct 2026). First posted on arXiv 6 Jun 2019.

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Citing papers per year: 2019: 1; 2020: 0; 2021: 117; 2022: 163; 2023: 205; 2024: 185; 2025: 230; 2026: 99.

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