M²VAE - Derivation of a Multi-Modal Variational Autoencoder Objective from the Marginal Joint Log-Likelihood
Korthals T (2019)
arXiv: 1903.07303v1.
Preprint | Englisch
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Einrichtung
Abstract / Bemerkung
This work gives an in-depth derivation of the trainable evidence lower bound obtained from the marginal joint log-Likelihood with the goal of training a Multi-Modal Variational Autoencoder (M$^2$VAE).
Appendix for the IEEE FUSION 2019 submission on multi-modal variational Autoencoders for sensor fusion
Appendix for the IEEE FUSION 2019 submission on multi-modal variational Autoencoders for sensor fusion
Stichworte
Deep Generative Models;
Variation Autoencoder;
Variation Auto Encoder;
Distributed Sensor Network;
Sensor Fusion;
multi-modal;
multi modal;
VAE;
publication;
sensorfusion;
fusion
Erscheinungsjahr
2019
Zeitschriftentitel
arXiv: 1903.07303v1
Page URI
https://pub.uni-bielefeld.de/record/2937523
Zitieren
Korthals T. M²VAE - Derivation of a Multi-Modal Variational Autoencoder Objective from the Marginal Joint Log-Likelihood. arXiv: 1903.07303v1. 2019.
Korthals, T. (2019). M²VAE - Derivation of a Multi-Modal Variational Autoencoder Objective from the Marginal Joint Log-Likelihood. arXiv: 1903.07303v1
Korthals, Timo. 2019. “M²VAE - Derivation of a Multi-Modal Variational Autoencoder Objective from the Marginal Joint Log-Likelihood”. arXiv: 1903.07303v1.
Korthals, T. (2019). M²VAE - Derivation of a Multi-Modal Variational Autoencoder Objective from the Marginal Joint Log-Likelihood. arXiv: 1903.07303v1.
Korthals, T., 2019. M²VAE - Derivation of a Multi-Modal Variational Autoencoder Objective from the Marginal Joint Log-Likelihood. arXiv: 1903.07303v1.
T. Korthals, “M²VAE - Derivation of a Multi-Modal Variational Autoencoder Objective from the Marginal Joint Log-Likelihood”, arXiv: 1903.07303v1, 2019.
Korthals, T.: M²VAE - Derivation of a Multi-Modal Variational Autoencoder Objective from the Marginal Joint Log-Likelihood. arXiv: 1903.07303v1. (2019).
Korthals, Timo. “M²VAE - Derivation of a Multi-Modal Variational Autoencoder Objective from the Marginal Joint Log-Likelihood”. arXiv: 1903.07303v1 (2019).
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Dieses Objekt ist durch das Urheberrecht und/oder verwandte Schutzrechte geschützt. [...]
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Open Access
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2019-09-20T16:09:28Z
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c3584803a65dda718e11dadcdfd5ae53
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