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Main Authors: Kristoffersen, Simen, Nordby, Peter Skaar, Malacarne, Sara, Ruocco, Massimiliano, Ortiz, Pablo
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2407.02258
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author Kristoffersen, Simen
Nordby, Peter Skaar
Malacarne, Sara
Ruocco, Massimiliano
Ortiz, Pablo
author_facet Kristoffersen, Simen
Nordby, Peter Skaar
Malacarne, Sara
Ruocco, Massimiliano
Ortiz, Pablo
contents We introduce SiamTST, a novel representation learning framework for multivariate time series. SiamTST integrates a Siamese network with attention, channel-independent patching, and normalization techniques to achieve superior performance. Evaluated on a real-world industrial telecommunication dataset, SiamTST demonstrates significant improvements in forecasting accuracy over existing methods. Notably, a simple linear network also shows competitive performance, achieving the second-best results, just behind SiamTST. The code is available at https://github.com/simenkristoff/SiamTST.
format Preprint
id arxiv_https___arxiv_org_abs_2407_02258
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle SiamTST: A Novel Representation Learning Framework for Enhanced Multivariate Time Series Forecasting applied to Telco Networks
Kristoffersen, Simen
Nordby, Peter Skaar
Malacarne, Sara
Ruocco, Massimiliano
Ortiz, Pablo
Machine Learning
Artificial Intelligence
We introduce SiamTST, a novel representation learning framework for multivariate time series. SiamTST integrates a Siamese network with attention, channel-independent patching, and normalization techniques to achieve superior performance. Evaluated on a real-world industrial telecommunication dataset, SiamTST demonstrates significant improvements in forecasting accuracy over existing methods. Notably, a simple linear network also shows competitive performance, achieving the second-best results, just behind SiamTST. The code is available at https://github.com/simenkristoff/SiamTST.
title SiamTST: A Novel Representation Learning Framework for Enhanced Multivariate Time Series Forecasting applied to Telco Networks
topic Machine Learning
Artificial Intelligence
url https://arxiv.org/abs/2407.02258