An enhanced particle filter for uncertainty quantification in neural networks

Carannante, G., Bouaynaya, N.C. and Mihaylova, L. orcid.org/0000-0001-5856-2223 (2021) An enhanced particle filter for uncertainty quantification in neural networks. In: de Villiers, P., de Waal, A. and Gustafsson, F., (eds.) 2021 IEEE 24th International Conference on Information Fusion (FUSION). 24th International Conference on Information Fusion (Fusion 2021), 01-04 Nov 2021, Sun City, South Africa. Institute of Electrical and Electronics Engineers . ISBN 9781665414272

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2021 ISIF. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy.
Keywords: Bayesian Learning; Particle Filtering; Neural Networks; Uncertainty Quantification
Dates:
  • Accepted: 9 August 2021
  • Published (online): 2 December 2021
  • Published: 2 December 2021
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Funding Information:
FunderGrant number
Engineering and Physical Sciences Research CouncilEP/T013265/1
Depositing User: Symplectic Sheffield
Date Deposited: 01 Sep 2021 10:14
Last Modified: 17 Dec 2021 07:48
Published Version: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumb...
Status: Published
Publisher: Institute of Electrical and Electronics Engineers
Refereed: Yes
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Embargoed until: 2 December 2022

Filename: Fusion_2021_Final_Version Enhanced PF.pdf

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