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arXiv · 2401.01242

Encoding Binary Events from Continuous Time Series in Rooted Trees using Contrastive Learning

Tobias Engelhardt Rasmussen·Siv Sørensen
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Abstract

Broadband infrastructure owners do not always know how their customers are connected in the local networks, which are structured as rooted trees. A recent study is able to infer the topology of a local network using discrete time series data from the leaves of the tree (customers). In this study we propose a contrastive approach for learning a binary event encoder from continuous time series data. As a preliminary result, we show that our approach has some potential in learning a valuable encoder.

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BibTeXRIS

Tobias Engelhardt Rasmussen, Siv Sørensen. 2024-01-02. Encoding Binary Events from Continuous Time Series in Rooted Trees using Contrastive Learning. https://arxiv.org/abs/2401.01242

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