OATAO - Open Archive Toulouse Archive Ouverte Open Access Week

Sparse Physics-based Gaussian Process for Multi-output Regression using Variational Inference

Chiplunkar, Ankit and Rachelson, Emmanuel and Colombo, Michele and Morlier, Joseph Sparse Physics-based Gaussian Process for Multi-output Regression using Variational Inference. (2016) In: International Conference on Pattern Recognition Applications and Methods, 24 February 2016 - 26 February 2016 (Rome, Italy).

[img]
Preview
(Document in English)

PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
491kB

Official URL: http://dx.doi.org/10.5220/0005700504370445

Abstract

In this paper a sparse approximation of inference for multi-output Gaussian Process models based on a Variational Inference approach is presented. In Gaussian Processes a multi-output kernel is a covariance function over correlated outputs. Using a general framework for constructing auto- and cross-covariance functions that are consistent with the physical laws, physical relationships among several outputs can be imposed. One major issue with Gaussian Processes is efficient inference, when scaling up-to large datasets. The issue of scaling becomes even more important when dealing with multiple outputs, since the cost of inference increases rapidly with the number of outputs. In this paper we combine the use of variational inference for efficient inference with multi-output kernels enforcing relationships between outputs. Results of the proposed methodology for synthetic data and real world applications are presented. The main contribution of this paper is the application and validation of our methodology on a dataset of real aircraft flight tests, while imposing knowledge of aircraft physics into the model.

Item Type:Conference or Workshop Item (Paper)
Additional Information:ISBN: 978-989-758-173-1
HAL Id:hal-01840472
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Other partners > Airbus (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Ecole nationale supérieure des Mines d'Albi-Carmaux - IMT Mines Albi (FRANCE)
Université de Toulouse > Institut National des Sciences Appliquées de Toulouse - INSA (FRANCE)
Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Laboratory name:
Statistics:download
Deposited By: Emmanuel Rachelson
Deposited On:12 Jul 2017 08:14

Repository Staff Only: item control page