Smooth Variational Graph Embeddings for Efficient Neural Architecture Search

Lukasik, Jovita; Friede, David; Zela, Arber; Hutter, Frank; Keuper, Margret

doi:10.1109/IJCNN52387.2021.9534092

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Smooth Variational Graph Embeddings for Efficient Neural Architecture Search

Lukasik, J., Friede, D., Zela, A., Hutter, F., & Keuper, M. (2021). Smooth Variational Graph Embeddings for Efficient Neural Architecture Search. In The International Joint Conference on Neural Networks (pp. 1-8). Piscataway, NJ: IEEE. doi:10.1109/IJCNN52387.2021.9534092.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0009-8824-5 Version Permalink: https://hdl.handle.net/21.11116/0000-000A-F174-3

Genre: Conference Paper

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Creators:
Lukasik, Jovita¹, Author
Friede, David¹, Author
Zela, Arber¹, Author
Hutter, Frank¹, Author
Keuper, Margret¹, Author

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1External Organizations, ou_persistent22

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Language(s): eng - English

Dates: Published Online: 2021

Publication Status: Published online

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Identifiers: BibTex Citekey: LukasikIJCNN2021
DOI: 10.1109/IJCNN52387.2021.9534092

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Title: The International Joint Conference on Neural Networks

Place of Event: Virtual Event

Start-/End Date: 2021-07-18 - 2021-07-22

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Title: The International Joint Conference on Neural Networks

Abbreviation : IJCNN 2021

Subtitle : Conference Proceedings

Source Genre: Proceedings

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Publ. Info: Piscataway, NJ : IEEE

Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1 - 8 Identifier: ISBN: 978-1-6654-3900-8