English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Group invariance principles for causal generative models

Besserve, M., Shajarisales, N., Schölkopf, B., & Janzing, D. (2018). Group invariance principles for causal generative models. In A. Storkey, & F. Perez-Cruz (Eds.), Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS) 2018 (pp. 557-565). PMLR. Retrieved from http://proceedings.mlr.press/v84/besserve18a.

Item is

Basic

show hide
Genre: Conference Paper

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Besserve, Michel1, 2, Author           
Shajarisales, Naji1, 2, Author           
Schölkopf, Bernhard2, Author           
Janzing, Dominik2, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647              

Content

show
hide
Free keywords: Abt. Schölkopf
 Abstract: -

Details

show
hide
Language(s): eng - English
 Dates: 2018
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: BesShaSchJan18
URI: http://proceedings.mlr.press/v84/besserve18a
 Degree: -

Event

show
hide
Title: 21st International Conference on Artificial Intelligence and Statistics (AISTATS 2018)
Place of Event: Playa Blanca, Lanzarote, Spain
Start-/End Date: 2018-04-09 - 2018-04-11

Legal Case

show

Project information

show

Source 1

show
hide
Title: Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS) 2018
Source Genre: Proceedings
 Creator(s):
Storkey, Amos1, Editor
Perez-Cruz, Fernando1, Editor
Affiliations:
1 External Organizations, ou_persistent22            
Publ. Info: PMLR
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 557 - 565 Identifier: URI: http://proceedings.mlr.press/v84/

Source 2

show
hide
Title: Proceedings of Machine Learning Research (PMLR)
Source Genre: Series
 Creator(s):
Affiliations:
Publ. Info: PMLR
Pages: - Volume / Issue: 84 Sequence Number: - Start / End Page: - Identifier: ISSN: 2640-3498