26 citations · 41 across the 5 of their papers we have counts for
5 papers
Self-Certifying Classification by Linearized Deep Assignment
Bastian Boll, Alexander Zeilmann, Stefania Petra +1
We propose a novel class of deep stochastic predictors for classifying metric data on graphs within the PAC-Bayes risk certification paradigm. Classifiers are realized as linearly…
Learning Linearized Assignment Flows for Image Labeling
Alexander Zeilmann, Stefania Petra, Christoph Schnörr
We introduce a novel algorithm for estimating optimal parameters of linearized assignment flows for image labeling. An exact formula is derived for the parameter gradient of any lo…
Assignment Flows for Data Labeling on Graphs: Convergence and Stability
Artjom Zern, Alexander Zeilmann, Christoph Schnörr
The assignment flow recently introduced in the J. Math. Imaging and Vision 58/2 (2017), constitutes a high-dimensional dynamical system that evolves on an elementary statistical ma…
End-to-End Learned Random Walker for Seeded Image Segmentation
Lorenzo Cerrone, Alexander Zeilmann, Fred A. Hamprecht
We present an end-to-end learned algorithm for seeded segmentation. Our method is based on the Random Walker algorithm, where we predict the edge weights of the underlying graph us…
Geometric Numerical Integration of the Assignment Flow
Alexander Zeilmann, Fabrizio Savarino, Stefania Petra +1
The assignment flow is a smooth dynamical system that evolves on an elementary statistical manifold and performs contextual data labeling on a graph. We derive and introduce the li…