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  Semantic Bottlenecks: Quantifying & Improving Inspectability of Deep Representations

Losch, M., Fritz, M., & Schiele, B. (2021). Semantic Bottlenecks: Quantifying & Improving Inspectability of Deep Representations. In Z. Akata, A. Geiger, & T. Sattler (Eds.), Pattern Recognition (pp. 15-29). Berlin: Springer.

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Genre: Conference Paper
Latex : Semantic Bottlenecks: {Q}uantifying \& Improving Inspectability of Deep Representations

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 Creators:
Losch, Max1, Author           
Fritz, Mario2, Author           
Schiele, Bernt1, Author           
Affiliations:
1Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society, ou_1116547              
2External Organizations, ou_persistent22              

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Language(s): eng - English
 Dates: 202020212021
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Losch_DAGM_GCP
 Degree: -

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Title: 42nd German Conference on Pattern Recognition
Place of Event: Tübingen, Germany
Start-/End Date: 2020-09-28 - 2020-10-01

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Title: Pattern Recognition
  Abbreviation : GCPR 2020
  Other : DAGM GCPR 2020
  Subtitle : 42nd DAGM German Conference, DAGM GCPR 2020 ; Tübingen, Germany, September 28 - October 1, 2020 ; Proceedings
Source Genre: Proceedings
 Creator(s):
Akata, Zeynep1, Editor           
Geiger, Andreas1, Editor
Sattler, Torsten1, Editor
Affiliations:
1 External Organizations, ou_persistent22            
Publ. Info: Berlin : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 15 - 29 Identifier: ISBN: 978-3-030-71277-8

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Title: Lecture Notes in Computer Science
  Abbreviation : LNCS
Source Genre: Series
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 12544 Sequence Number: - Start / End Page: - Identifier: -