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  A variational-autoencoder approach to solve the hidden profile task in hybrid human-machine teams

Pescetelli, N., Reichert, P., & Rutherford, A. (2022). A variational-autoencoder approach to solve the hidden profile task in hybrid human-machine teams. PLoS ONE, 17(8): e0272168. doi:10.1371/journal.pone.0272168.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0009-5E85-8 Version Permalink: https://hdl.handle.net/21.11116/0000-000C-EF40-F
Genre: Journal Article

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https://doi.org/10.1371/journal.pone.0272168 (Publisher version)
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https://figshare.com/articles/figure/Predictive_functions_/20420088 (Supplementary material)
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https://figshare.com/articles/figure/Sigmoid_function_calculating_rain_probability_/20420091 (Supplementary material)
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 Creators:
Pescetelli, Niccolò1, Author           
Reichert, Patrik1, Author
Rutherford, Alex2, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Center for Humans and Machines, Max Planck Institute for Human Development, Max Planck Society, ou_3017589              

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Language(s): eng - English
 Dates: 2022
 Publication Status: Issued
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 Rev. Type: Peer
 Identifiers: DOI: 10.1371/journal.pone.0272168
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Title: PLoS ONE
Source Genre: Journal
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Pages: - Volume / Issue: 17 (8) Sequence Number: e0272168 Start / End Page: - Identifier: -