Engelmann, Nicolai ; Linzner, Dominik ; Koeppl, Heinz (2022):
Continuous Time Bayesian Networks with Clocks. (Publisher's Version)
In: Proceedings of Machine Learning Research, 119, In: Proceedings of the 37th International Conference on Machine Learning, pp. 2912-2921,
Darmstadt, PMLR, 37th International Conference on Machine Learning, Online, 12.-18.07.2020, DOI: 10.26083/tuprints-00021516,
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Item Type: | Conference or Workshop Item |
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Origin: | Secondary publication service |
Status: | Publisher's Version |
Title: | Continuous Time Bayesian Networks with Clocks |
Language: | English |
Abstract: | Structured stochastic processes evolving in continuous time present a widely adopted framework to model phenomena occurring in nature and engineering. However, such models are often chosen to satisfy the Markov property to maintain tractability. One of the more popular of such memoryless models are Continuous Time Bayesian Networks (CTBNs). In this work, we lift its restriction to exponential survival times to arbitrary distributions. Current extensions achieve this via auxiliary states, which hinder tractability. To avoid that, we introduce a set of node-wise clocks to construct a collection of graph-coupled semi-Markov chains. We provide algorithms for parameter and structure inference, which make use of local dependencies and conduct experiments on synthetic data and a data-set generated through a benchmark tool for gene regulatory networks. In doing so, we point out advantages compared to current CTBN extensions. |
Book Title: | Proceedings of the 37th International Conference on Machine Learning |
Series: | Proceedings of Machine Learning Research |
Series Volume: | 119 |
Place of Publication: | Darmstadt |
Publisher: | PMLR |
Classification DDC: | 000 Allgemeines, Informatik, Informationswissenschaft > 004 Informatik 600 Technik, Medizin, angewandte Wissenschaften > 620 Ingenieurwissenschaften und Maschinenbau |
Divisions: | 18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Bioinspired Communication Systems 18 Department of Electrical Engineering and Information Technology > Self-Organizing Systems Lab |
Event Title: | 37th International Conference on Machine Learning |
Event Location: | Online |
Event Dates: | 12.-18.07.2020 |
Date Deposited: | 20 Jul 2022 13:43 |
Last Modified: | 12 Apr 2023 07:49 |
DOI: | 10.26083/tuprints-00021516 |
Corresponding Links: | |
URN: | urn:nbn:de:tuda-tuprints-215165 |
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/21516 |
PPN: | 497909405 |
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