Theory and Applications of Differential Equation Methods for Graph-based Learning
Jeremy Budd (TU Delft - Mathematical Physics)
J.L.A. Dubbeldam – Promotor (TU Delft - Mathematical Physics)
Y. van Gennip – Copromotor (TU Delft - Mathematical Physics)
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Abstract
A large number of modern learning problems involve working with highly interrelated and interconnected data. Graph-based learning is an emerging technique for approaching such problems, by representing this data as a graph (a.k.a. a network). That is, the points of data are represented by the vertices of the graph, and then the edges linking these vertices represent the relationships between the points of data. This provides a unified perspective for thinking about all sorts of interrelated data: the vertices could represent pixels in an image or people in a social network, and the underlying framework would be the same...