Handling incomplete heterogeneous data using VAEs

Nazábal, Alfredo; Olmos, Pablo M.; Ghahramani, Zoubin; Valera, Isabel

doi:10.1016/j.patcog.2020.107501

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Journal Article

Handling incomplete heterogeneous data using VAEs

MPS-Authors

/persons/resource/persons144952

Valera, Isabel
Max Planck Research Group Probabilistic Learning, Max Planck Institute for Intelligent Systems, Max Planck Society;
External Organizations;

External Resource

https://doi.org/10.1016/j.patcog.2020.107501
(Publisher version)

https://doi.org/10.48550/arXiv.1807.03653
(Preprint)

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

There are no public fulltexts stored in PuRe

Supplementary Material (public)

There is no public supplementary material available

Citation

Nazábal, A., Olmos, P. M., Ghahramani, Z., & Valera, I. (2020). Handling incomplete heterogeneous data using VAEs. Pattern Recognition, 107: 107501. doi:10.1016/j.patcog.2020.107501.

Cite as: https://hdl.handle.net/21.11116/0000-000C-DE29-D

Abstract

There is no abstract available