Statistical methods for topology inference, denoising, and bootstrapping in networks
Quite often, the data we observe can be effectively represented using graphs. The underlying structure of the resulting graph, however, might contain noise and does not always hold constant across scales. With the right tools, we could possibly address these two problems. This thesis focuses on deve...
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| Language: | en_US |
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2019
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| Online Access: | https://hdl.handle.net/2144/33117 |