DeepCoDA: Personalized interpretability for compositional health data

Quinn, Thomas, Nguyen, Dang, Rana, Santu, Gupta, Sunil and Venkatesh, Svetha 2020, DeepCoDA: Personalized interpretability for compositional health data, in ICML 2020 : Proceedings of the 37th International Conference on Machine Learning, [The Conference], [Online], pp. 7833-7842.

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Title DeepCoDA: Personalized interpretability for compositional health data
Author(s) Quinn, ThomasORCID iD for Quinn, Thomas orcid.org/0000-0003-0286-6329
Nguyen, DangORCID iD for Nguyen, Dang orcid.org/0000-0002-0401-988X
Rana, SantuORCID iD for Rana, Santu orcid.org/0000-0003-2247-850X
Gupta, SunilORCID iD for Gupta, Sunil orcid.org/0000-0002-3308-1930
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Conference name Machine Learning. Conference (2020 : 37th : Virtual Conference)
Conference location Online
Conference dates 11-12 Jul. 2020
Title of proceedings ICML 2020 : Proceedings of the 37th International Conference on Machine Learning
Publication date 2020
Start page 7833
End page 7842
Total pages 14
Publisher [The Conference]
Place of publication [Online]
ISBN 9781713821120
Language eng
Indigenous content off
HERDC Research category E1 Full written paper - refereed
Grant ID FL170100006
Persistent URL http://hdl.handle.net/10536/DRO/DU:30151487

Document type: Conference Paper
Collection: A2I2 (Applied Artificial Intelligence Institute)
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