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Author Title Type [ Year(Asc)]
Filters: Author is Savarino, F.  [Clear All Filters]
2020
Zeilmann, A, Savarino, F, Petra, S and Schnörr, C (2020). Geometric Numerical Integration of the Assignment Flow. Inverse Problems. 36 034004 (33pp)
2019
Savarino, F and Schnörr, C (2019). Continuous-Domain Assignment Flows. preprint: arXiv. https://arxiv.org/abs/1910.07287
Zeilmann, A, Savarino, F, Petra, S and Schnörr, C (2019). Geometric Numerical Integration of the Assignment Flow. Inverse Problems. https://doi.org/10.1088/1361-6420/ab2772
Hühnerbein, R, Savarino, F, Petra, S and Schnörr, C (2019). Learning Adaptive Regularization for Image Labeling Using Geometric Assignment. preprint: arXiv. https://arxiv.org/abs/1910.09976
Hühnerbein, R, Savarino, F, Petra, S and Schnörr, C (2019). Learning Adaptive Regularization for Image Labeling Using Geometric Assignment. Proc. SSVM. Springer
Savarino, F and Schnörr, C (2019). A Variational Perspective on the Assignment Flow. Proc. SSVM. Springer
2018
Zeilmann, A, Savarino, F, Petra, S and Schnörr, C (2018). Geometric Numerical Integration of the Assignment Flow. preprint: arXiv. https://arxiv.org/abs/1810.06970
Hühnerbein, R, Savarino, F, Aström, F and Schnörr, C (2018). Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment. SIAM J. Imaging Science. 11 1317–1362. https://epubs.siam.org/doi/abs/10.1137/17M1150669
2017
Zisler, M, Savarino, F, Petra, S and Schnörr, C (2017). Gradient Flows on a Riemannian Submanifold for Discrete Tomography. Proc. GCPR
Hühnerbein, R, Savarino, F, Aström, F and Schnörr, C (2017). Image Labeling Based on Graphical Models Using Wasserstein Messages and Geometric Assignment. http://arxiv.org/abs/1710.01493
Aström, F, Hühnerbein, R, Savarino, F, Recknagel, J and Schnörr, C (2017). MAP Image Labeling Using Wasserstein Messages and Geometric Assignment. Proc. SSVM. Springer. 10302
Savarino, F, Hühnerbein, R, Aström, F, Recknagel, J and Schnörr, C (2017). Numerical Integration of Riemannian Gradient Flows for Image Labeling. Proc. SSVM. Springer. 10302