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  Resisting Adversarial Attacks Using Gaussian Mixture Variational Autoencoders

Ghosh, P., Losalka, A., & Black, M. J. (2019). Resisting Adversarial Attacks Using Gaussian Mixture Variational Autoencoders. In The Thirty-Third AAAI Conference on Artificial Intelligence, the Thirty-First Innovative Applications of Artificial Intelligence Conference, the Ninth AAAI Symposium on Educational Advances in Artificial Intelligence (pp. 541-548). Palo Alto, CA: AAAI Press. doi:10.1609/aaai.v33i01.3301541.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0006-E4AE-5 Version Permalink: https://hdl.handle.net/21.11116/0000-0009-6EF7-6
Genre: Conference Paper

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 Creators:
Ghosh, Partha1, Author           
Losalka, Arpan2, Author
Black, Michael J.1, Author           
Affiliations:
1Dept. Perceiving Systems, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497642              
2External Organizations, ou_persistent22              

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Free keywords: Abt. Black
 Abstract: -

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Language(s): eng - English
 Dates: 2019-07-172019-07-23
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: ghosh2019resisting
DOI: 10.1609/aaai.v33i01.3301541
 Degree: -

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Title: Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019), Thirty-First Innovative Applications of Artificial Intelligence Conference (IAAI 2019), Ninth AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI 2019)
Place of Event: Honolulu, HI
Start-/End Date: 2019-01-27 - 2019-02-01

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Title: The Thirty-Third AAAI Conference on Artificial Intelligence, the Thirty-First Innovative Applications of Artificial Intelligence Conference, the Ninth AAAI Symposium on Educational Advances in Artificial Intelligence
  Other : Proceedings of the AAAI Conference on Artificial Intelligence, 33
  Other : AAAI-19/IAAI-19/EAAI-19 Proceedings
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: Palo Alto, CA : AAAI Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 541 - 548 Identifier: ISBN: 978-1-57735-809-1
ISSN: 2159-5399
ISSN: 2374-3468
URI: https://aaai.org/Library/AAAI/aaai19contents.php
URI: https://aaai.org/ojs/index.php/AAAI/issue/view/246