auto-encoding-variational-bayes-2022-022

Diederik P. Kingma, Max Welling

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auto-encoding-variational-bayes-2022-022

Diederik P. Kingma, Max WellingUFTAN UNIVERSITYStatistics2022

Abstract

This record links to the variational autoencoder paper, which introduces a practical approach to variational inference with neural networks. It supports realistic testing of statistics, generative modelling, and advanced research metadata.

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Author: Diederik P. Kingma, Max Welling
Supervisor: Prof. Salihu B. Usman
Faculty: Science
Department: Statistics
Document type: Final Year Project
Year: 2022
Keywords: variational autoencoders, Bayesian inference, generative models, latent variables, probabilistic learning
Access: Metadata
License: all_rights_reserved

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Auto-generated from the record metadata: authors, journal title, DOI, volume, issue/serial, pages and publication date. Review before final academic use.

Diederik P. Kingma, Max Welling (2026). auto-encoding-variational-bayes-2022-022 [Final Year Project]. UFTAN UNIVERSITY. https://inrepscholar.com/uftan-university/projects/961

Source fields used: Diederik P. Kingma, Max Welling

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