Assignment Flows

Christoph Schnörr ()
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Christoph Schnörr: Heidelberg University, Institute of Applied Mathematics

Chapter Chapter 8 in Handbook of Variational Methods for Nonlinear Geometric Data, 2020, pp 235-260 from Springer

Abstract: Abstract Assignment flows comprise basic dynamical systems for modeling data labeling and related machine learning tasks in supervised and unsupervised scenarios. They provide adaptive time-variant extensions of established discrete graphical models and a basis for the design and better mathematical understanding of hierarchical networks, using methods from information (differential) geometry, geometric numerical integration, statistical inference, optimal transport and control. This chapter introduces the framework by means of the image labeling problem and outlines directions of current and further research.

Date: 2020
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DOI: 10.1007/978-3-030-31351-7_8

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