Auto-Encoding Variational Bayes

Kingma, D. P., & Welling, M. (2014). Auto-Encoding Variational Bayes.

Type

Preprint

Intellectual base

Grey literature

Year

2014

Link

https://arxiv.org/abs/1312.6114

Cited from

statistics_experimental_design

Cited by

1 citation across 1 artifact.

Each citation links to the sentence it supports in the citing article.

Primes

• Dimensionality Reduction

  • This sourceIntroduces the variational autoencoder (VAE) generative model and reparameterization trick. (Removed from marker 075: the paper introduces VAEs as a generative model but does not substantiate the overfitting/non-generalization claim; retained as bibliography reference for VAEs.) Bibliography-only.

Verification

This reference passed the adversarial substantiation pipeline: it was checked to exist and to support the claim it is attached to. See how references were verified.

Registry ID ref:710257bd9599 · see in the full table