Analyzing graph time series using a generative model

Ye, C., Wilson, R. C. orcid.org/0000-0001-7265-3033 and Hancock, E. R. orcid.org/0000-0003-4496-2028 (2016) Analyzing graph time series using a generative model. In: Davis, L., Bimbo, A. Del and Lovell, B., (eds.) 2016 23rd International Conference on Pattern Recognition (ICPR). IEEE Computer Society , Los Alamitos, CA, USA , pp. 3338-3343.

Metadata

Item Type: Proceedings Paper
Authors/Creators:
Editors:
  • Davis, L.
  • Bimbo, A. Del
  • Lovell, B.
Copyright, Publisher and Additional Information:

©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works.
Keywords: Analytical models,Complexity theory,Computational modeling,Data models,Entropy,Probabilistic logic,Probability distribution
Dates:
  • Published: 1 December 2016
Institution: The University of York
Academic Units: The University of York > Faculty of Sciences (York) > Computer Science (York)
Depositing User: Pure (York)
Date Deposited: 28 Jul 2016 09:42
Last Modified: 08 Apr 2025 17:18
Published Version: https://doi.org/10.1109/ICPR.2016.7900149
Status: Published
Publisher: IEEE Computer Society
Identification Number: 10.1109/ICPR.2016.7900149
Open Archives Initiative ID (OAI ID):

Download

Accepted Version

Filename: ICPR16_0589_MS.pdf

Description: ICPR16_0589_MS

CLICK TO DOWNLOAD [thumbnail of ICPR16_0589_MS]

Export

Statistics


CORE (COnnecting REpositories)