Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 2 of 2 for “"Bayesian non-parametrics"”.
-
Non-parametric modelling of signals on graphs
… hypothesise that Gaussian processes, a class of Bayesian non-parametric models, are particularly well suited for modelling data on graph domains. To provide evidence for this hypothesis, I demonstrate the merits of Bayesian non-parametric modelling for graph data by deriving Gaussian process …
-
Hierarchical Inference in Gaussian Processes
… machine learning which relies on the Bayesian interpretation on probability. The starting requirement for these models is that all unknowns are treated as random variables with their own respective probability distributions. The central idea behind hierarchical modelling is that …