Difference between revisions of "Generative Approach for Multivariate Signals"

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|Summary=.
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|Summary=The topic focuses on generative models (VAE) for CAN-bus data and investigating the representation learning capabilities of such techniques
|Supervisor=.
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|Keywords=VAE, Time-series data, Streaming data, MAR
|Status=Internal Draft
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|TimeFrame=2021 Fall - 2022 Summer
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|References=https://papers.nips.cc/paper/8789-time-series-generative-adversarial-networks.pdf
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https://openreview.net/pdf?id=Sy2fzU9gl
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https://www.sciencedirect.com/science/article/pii/S092658051930367X
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|Supervisor=Kunru Chen, Abdallah Alabdallah, Thorsteinn Rögnvaldsson
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|Level=Master
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|Status=Open
 
}}
 
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Latest revision as of 16:27, 12 October 2023

Title Generative Approach for Multivariate Signals
Summary The topic focuses on generative models (VAE) for CAN-bus data and investigating the representation learning capabilities of such techniques
Keywords VAE, Time-series data, Streaming data, MAR
TimeFrame 2021 Fall - 2022 Summer
References https://papers.nips.cc/paper/8789-time-series-generative-adversarial-networks.pdf

https://openreview.net/pdf?id=Sy2fzU9gl

https://www.sciencedirect.com/science/article/pii/S092658051930367X

Prerequisites
Author
Supervisor Kunru Chen, Abdallah Alabdallah, Thorsteinn Rögnvaldsson
Level Master
Status Open