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title:(Laplacian AND Autoencoders AND for AND Learning AND Stochastic AND Representations)

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1 Conference paper

Laplacian Autoencoders for Learning Stochastic Representations

Miani, Marco; Warburg, Frederik; Moreno-Muñoz, Pablo; Detlefsen, Nicke Skafte; Hauberg, Søren

Proceedings of 36<sup>th</sup> Conference on Neural Information Processing Systems — 2022

Established methods for unsupervised representation learning such as variational autoencoders produce none or poorly calibrated uncertainty estimates making it difficult to evaluate if learned representations are stable and reliable. In this work, we present a Bayesian autoencoder for unsupervised

Year: 2022

Language: English

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2 Preprint article

Laplacian Autoencoders for Learning Stochastic Representations

Established methods for unsupervised representation learning such as variational autoencoders produce none or poorly calibrated uncertainty estimates making it difficult to evaluate if learned representations are stable and reliable. In this work, we present a Bayesian autoencoder for unsupervised

Year: 2022

Language: Undetermined

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