Uncertainty estimation for multi-view data: the power of seeing the whole picture

Myong Chol Jung, He Zhao, Joanna Dipnall, Belinda Gabbe, Lan Du

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

5 Citations (Scopus)


Uncertainty estimation is essential to make neural networks trustworthy in real-world applications. Extensive research efforts have been made to quantify and reduce predictive uncertainty. However, most existing works are designed for unimodal data, whereas multi-view uncertainty estimation has not been sufficiently investigated. Therefore, we propose a new multi-view classification framework for better uncertainty estimation and out-of-domain sample detection, where we associate each view with an uncertainty-aware classifier and combine the predictions of all the views in a principled way. The experimental results with real-world datasets demonstrate that our proposed approach is an accurate, reliable, and well-calibrated classifier, which predominantly outperforms the multi-view baselines tested in terms of expected calibration error, robustness to noise, and accuracy for the in-domain sample classification and the out-of-domain sample detection tasks.

Original languageEnglish
Title of host publicationAdvances in Neural Information Processing Systems 35 (NeurIPS 2022)
EditorsS. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, A. Oh
Place of PublicationSan Diego CA USA
PublisherNeural Information Processing Systems (NIPS)
Number of pages14
ISBN (Electronic)9781713871088
Publication statusPublished - 2022
EventAdvances in Neural Information Processing Systems 2022 - New Orleans Convention Center, New Orleans, United States of America
Duration: 28 Nov 20229 Dec 2022
Conference number: 36th
https://proceedings.neurips.cc/paper_files/paper/2022 (Proceedings)
https://openreview.net/group?id=NeurIPS.cc/2022/Conference (Peer Reviews)

Publication series

NameAdvances in Neural Information Processing Systems
PublisherNeural Information Processing Systems (NIPS)
ISSN (Print)1049-5258


ConferenceAdvances in Neural Information Processing Systems 2022
Abbreviated titleNeurIPS 2022
Country/TerritoryUnited States of America
CityNew Orleans
Internet address

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