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Found 4 papers, 2 papers with code
End-to-End Learned Random Walker for Seeded Image Segmentation
We present an end-to-end learned algorithm for seeded segmentation.
Self-Certifying Classification by Linearized Deep Assignment
We propose a novel class of deep stochastic predictors for classifying metric data on graphs within the PAC-Bayes risk certification paradigm.
Assignment Flows for Data Labeling on Graphs: Convergence and Stability
The assignment flow recently introduced in the J.
Learning Linearized Assignment Flows for Image Labeling
An exact formula is derived for the parameter gradient of any loss function that is constrained by the linear system of ODEs determining the linearized assignment flow.
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