Deep transfer learning for classification of time-delayed Gaussian networks
In this paper, we propose deep transfer learning for classifcation of Gaussian networks with time-delayed regulations. To ensure robust signaling, most real world problems from related domains have inherent alternate pathways that can be learned incrementally from a stable form of the baseline. In t...
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Main Authors: | , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2016
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/82815 http://hdl.handle.net/10220/40335 |
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Institution: | Nanyang Technological University |
Language: | English |
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