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Approximate variational inference has shown to be a powerful tool for modeling unknown complex probability distributions.
Auto-encoding variational bayes
Kingma, Diederik P and Welling, Max · 2013
Earlier work this paper cites.
Learning stochastic recurrent networks
Bayer, Justin and Osendorfer, Christian · 2014
Earlier work this paper cites.
A review of novelty detection
Pimentel, Marco AF, Clifton, David A, Clifton, Lei, and Tarassenko, Lionel · 2014
Earlier work this paper cites.
Stochastic backpropagation and approximate inference in deep generative models
Rezende, Danilo J., Mohamed, Shakir, and Wierstra, Daan · 2014
Cited alongside, same era.
Variational autoencoder based anomaly detection using reconstruction probability
An, Jinwon and Cho, Sungzoon · 2015
Cited alongside, same era.
A recurrent latent variable model for sequential data
Chung, Junyoung, Kastner, Kyle, Dinh, Laurent, Goel, Kratarth, Courville, Aaron C., and Bengio, Yoshua · 2015
Later among the works it cites.
Robust detection of anomalies via sparse methods
Milacski, Zoltán Á, Ludersdorfer, Marvin, Lorincz, András, and van der Smagt, Patrick · 2015
Later among the works it cites.
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