English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
 Local TagsRelease HistoryDetailsSummary
  Resampled Priors for Variational Autoencoders

Bauer, M., & Mnih, A. (2019). Resampled Priors for Variational Autoencoders. In K. Chaudhuri, & M. Sugiyama (Eds.), Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS) 2019 (pp. 66-75). PMLR. Retrieved from http://proceedings.mlr.press/v89/bauer19a.html.

Item is

 

show all hide all

Basic

show hide
Item Permalink: https://hdl.handle.net/21.11116/0000-0006-E11C-D Version Permalink: https://hdl.handle.net/21.11116/0000-0006-E11D-C
Genre: Conference Paper

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Bauer, M.1, Author           
Mnih, A.2, Author
Affiliations:
1Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647              
2External Organizations, ou_persistent22              

Content

show
hide
Free keywords: Abt. Schölkopf
 Abstract: -

Details

show
hide
Language(s): eng - English
 Dates: 2019
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: BauMni18
URI: http://proceedings.mlr.press/v89/bauer19a.html
 Degree: -

Event

show
hide
Title: 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019)
Place of Event: Naha, Okinawa, Japan
Start-/End Date: 2019-04-16 - 2019-04-18

Legal Case

show

Project information

show

Source 1

show
hide
Title: Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS) 2019
Source Genre: Proceedings
 Creator(s):
Chaudhuri, K.1, Editor
Sugiyama, M.1, Editor
Affiliations:
1 External Organizations, ou_persistent22            
Publ. Info: PMLR
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 66 - 75 Identifier: URI: http://proceedings.mlr.press/v89/

Source 2

show
hide
Title: Proceedings of Machine Learning Research (PMLR)
Source Genre: Series
 Creator(s):
Affiliations:
Publ. Info: PMLR
Pages: - Volume / Issue: 89 Sequence Number: - Start / End Page: - Identifier: ISSN: 2640-3498