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MATRIX COMPLETION WITH VARIATIONAL GRAPH AUTOENCODERS: APPLICATION IN HYPERLOCAL AIR QUALITY INFERENCE

Abstract: 

Inferring air quality from a limited number of observations is an essential task for monitoring and controlling air pollution. Existing inference methods typically use low spatial resolution data collected by fixed monitoring stations and infer the concentration of air pollutants using additional types of data, e.g., meteorological and traffic information. In this work, we focus on street-level air quality inference by utilizing data collected by mobile stations. We formulate air quality inference in this setting as a graph-based matrix completion problem and propose a novel variational model based on graph convolutional autoencoders. Our model captures effectively the spatio-temporal correlation of the measurements and does not depend on the availability of additional information apart from the street-network topology. Experiments on a real air quality dataset, collected with mobile stations, shows that the proposed model outperforms state-of-the-art approaches.

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Paper Details

Authors:
Evaggelia Tsiligianni, Angel Lopez Aguirre, Valerio Panzica La Manna, Frank Pasveer, Wilfried Philips, Nikos Deligiannis
Submitted On:
11 May 2019 - 1:38am
Short Link:
Type:
Poster
Event:
Presenter's Name:
Tien Huu Do, Evaggelia Tsiligianni
Paper Code:
3765
Document Year:
2019
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Document Files

icassp19_poster.pdf

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[1] Evaggelia Tsiligianni, Angel Lopez Aguirre, Valerio Panzica La Manna, Frank Pasveer, Wilfried Philips, Nikos Deligiannis, "MATRIX COMPLETION WITH VARIATIONAL GRAPH AUTOENCODERS: APPLICATION IN HYPERLOCAL AIR QUALITY INFERENCE", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4435. Accessed: Aug. 25, 2019.
@article{4435-19,
url = {http://sigport.org/4435},
author = {Evaggelia Tsiligianni; Angel Lopez Aguirre; Valerio Panzica La Manna; Frank Pasveer; Wilfried Philips; Nikos Deligiannis },
publisher = {IEEE SigPort},
title = {MATRIX COMPLETION WITH VARIATIONAL GRAPH AUTOENCODERS: APPLICATION IN HYPERLOCAL AIR QUALITY INFERENCE},
year = {2019} }
TY - EJOUR
T1 - MATRIX COMPLETION WITH VARIATIONAL GRAPH AUTOENCODERS: APPLICATION IN HYPERLOCAL AIR QUALITY INFERENCE
AU - Evaggelia Tsiligianni; Angel Lopez Aguirre; Valerio Panzica La Manna; Frank Pasveer; Wilfried Philips; Nikos Deligiannis
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4435
ER -
Evaggelia Tsiligianni, Angel Lopez Aguirre, Valerio Panzica La Manna, Frank Pasveer, Wilfried Philips, Nikos Deligiannis. (2019). MATRIX COMPLETION WITH VARIATIONAL GRAPH AUTOENCODERS: APPLICATION IN HYPERLOCAL AIR QUALITY INFERENCE. IEEE SigPort. http://sigport.org/4435
Evaggelia Tsiligianni, Angel Lopez Aguirre, Valerio Panzica La Manna, Frank Pasveer, Wilfried Philips, Nikos Deligiannis, 2019. MATRIX COMPLETION WITH VARIATIONAL GRAPH AUTOENCODERS: APPLICATION IN HYPERLOCAL AIR QUALITY INFERENCE. Available at: http://sigport.org/4435.
Evaggelia Tsiligianni, Angel Lopez Aguirre, Valerio Panzica La Manna, Frank Pasveer, Wilfried Philips, Nikos Deligiannis. (2019). "MATRIX COMPLETION WITH VARIATIONAL GRAPH AUTOENCODERS: APPLICATION IN HYPERLOCAL AIR QUALITY INFERENCE." Web.
1. Evaggelia Tsiligianni, Angel Lopez Aguirre, Valerio Panzica La Manna, Frank Pasveer, Wilfried Philips, Nikos Deligiannis. MATRIX COMPLETION WITH VARIATIONAL GRAPH AUTOENCODERS: APPLICATION IN HYPERLOCAL AIR QUALITY INFERENCE [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4435