Bayesian Inference in Recurrent Explicit Duration Switching Linear Dynamical Systems

Bibliographic Details
Title: Bayesian Inference in Recurrent Explicit Duration Switching Linear Dynamical Systems
Authors: Słupiński, Mikołaj, Lipiński, Piotr
Publication Year: 2024
Collection: Computer Science
Mathematics
Statistics
Subject Terms: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Mathematics - Dynamical Systems, Statistics - Machine Learning
More Details: In this paper, we propose a novel model called Recurrent Explicit Duration Switching Linear Dynamical Systems (REDSLDS) that incorporates recurrent explicit duration variables into the rSLDS model. We also propose an inference and learning scheme that involves the use of P\'olya-gamma augmentation. We demonstrate the improved segmentation capabilities of our model on three benchmark datasets, including two quantitative datasets and one qualitative dataset.
Document Type: Working Paper
Access URL: http://arxiv.org/abs/2411.04280
Accession Number: edsarx.2411.04280
Database: arXiv
More Details
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