IEEE_TNNLS_20017_Learning_methods_dynamic_TM-code.zip (50.17 kB)

Code for "Learning methods for dynamic topic modeling in automated behavior analysis"

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posted on 08.01.2018 by Olga Isupova, Danil Kuzin, Lyudmila Mihaylova
This is source code for the algorithms presented in the paper "Learning Methods for Dynamic Topic Modeling in Automated Behavior Analysis" by Olga Isupova, Danil Kuzin, Lyudmila Mihaylova. Published in IEEE Transactions on Neural Networks and Learning Systems, 2017. DOI: 10.1109/TNNLS.2017.2735364.

Two learning methods for the Markov Clustering Topic Model (MCTM) are developed - Expectation-Maximisation (EM) algorithm and Variational Bayes (VB) inference.
Implementation is done in Matlab.

Funding

Bayesian Tracking and Reasoning over Time under Grant EP/K021516/1 and EC Seventh Framework Programme [FP7 2013-2017] TRAcking in compleX sensor systems under Grant 607400

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