Variational Gaussian filtering via Wasserstein gradient flows

Thumbnail Image

Access rights

openAccess
acceptedVersion

URL

Journal Title

Journal ISSN

Volume Title

A4 Artikkeli konferenssijulkaisussa
This publication is imported from Aalto University research portal.
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)

Authors

Date

2023

Department

Department of Electrical Engineering and Automation

Major/Subject

Mcode

Degree programme

Language

en

Pages

5

Series

31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings, pp. 1838-1842, European Signal Processing Conference

Abstract

We present a novel approach to approximate Gaussian and mixture-of-Gaussians filtering. Our method relies on a variational approximation via a gradient-flow representation. The gradient flow is derived from a Kullback-Leibler discrepancy minimization on the space of probability distributions equipped with the Wasserstein metric. We outline the general method and show its competitiveness in posterior representation and parameter estimation on two state-space models for which Gaussian approximations typically fail: systems with multiplicative noise and multi-modal state distributions.

Description

Funding Information: Adrien Corenflos is funded by the Academy of Finland project 321891 (ADAFUME). Hany Abdulsamad is funded by the Finnish Center for Artificial Intelligence (FCAI). Publisher Copyright: © 2023 European Signal Processing Conference, EUSIPCO. All rights reserved.

Keywords

Kalman filtering, state-space models, variational inference, Wasserstein gradient flow

Other note

DOI

10.23919/EUSIPCO58844.2023.10289853

Citation

Corenflos, A & Abdulsamad, H 2023, Variational Gaussian filtering via Wasserstein gradient flows. in 31st European Signal Processing Conference, EUSIPCO 2023 - Proceedings. European Signal Processing Conference, European Association For Signal and Image Processing, pp. 1838-1842, European Signal Processing Conference, Helsinki, Finland, 04/09/2023. https://doi.org/10.23919/EUSIPCO58844.2023.10289853

Permanent link to this item

https://urn.fi/URN:NBN:fi:aalto-202401041218

Collections

[article-cris] Sähkötekniikan korkeakoulu / ELEC