Daniel Tenbrinck

According to our database, Daniel Tenbrinck authored at least 30 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Hypergraph p-Laplacians and Scale Spaces.

Ariane Fazeny, Daniel Tenbrinck, Kseniia Lukin, Martin Burger

J. Math. Imaging Vis., August, 2024

The Infinity Laplacian Eigenvalue Problem: Reformulation and a Numerical Scheme.

Farid Bozorgnia, Leon Bungert, Daniel Tenbrinck

J. Sci. Comput., February, 2024

2023

Resolution-Invariant Image Classification Based on Fourier Neural Operators.

Samira Kabri, Tim Roith, Daniel Tenbrinck, Martin Burger

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2023

Hypergraph p-Laplacians, Scale Spaces, and Information Flow in Networks.

Ariane Fazeny, Daniel Tenbrinck, Martin Burger

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2023

2022

A Bregman Learning Framework for Sparse Neural Networks.

Leon Bungert, Tim Roith, Daniel Tenbrinck, Martin Burger

J. Mach. Learn. Res., 2022

2021

Fenchel Duality Theory and a Primal-Dual Algorithm on Riemannian Manifolds.

Ronny Bergmann, Roland Herzog, Maurício Silva Louzeiro, Daniel Tenbrinck, José Vidal-Núñez

Found. Comput. Math., 2021

Neural Architecture Search via Bregman Iterations.

Leon Bungert, Tim Roith, Daniel Tenbrinck, Martin Burger

CoRR, 2021

Identifying untrustworthy predictions in neural networks by geometric gradient analysis.

Leo Schwinn, An Nguyen, René Raab, Leon Bungert, Daniel Tenbrinck, Dario Zanca, Martin Burger, Björn M. Eskofier

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

CLIP: Cheap Lipschitz Training of Neural Networks.

Leon Bungert, René Raab, Tim Roith, Leo Schwinn, Daniel Tenbrinck

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2021

Dynamically Sampled Nonlocal Gradients for Stronger Adversarial Attacks.

Leo Schwinn, An Nguyen, René Raab, Dario Zanca, Bjoern M. Eskofier, Daniel Tenbrinck, Martin Burger

Proceedings of the International Joint Conference on Neural Networks, 2021

2020

Sampled Nonlocal Gradients for Stronger Adversarial Attacks.

Leo Schwinn, Daniel Tenbrinck, An Nguyen, René Raab, Martin Burger, Bjoern M. Eskofier

CoRR, 2020

2019

Fenchel Duality for Convex Optimization and a Primal Dual Algorithm on Riemannian Manifolds.

Ronny Bergmann, Roland Herzog, Daniel Tenbrinck, José Vidal-Núñez

CoRR, 2019

Variational Graph Methods for Efficient Point Cloud Sparsification.

Daniel Tenbrinck, Fjedor Gaede, Martin Burger

CoRR, 2019

Computing Nonlinear Eigenfunctions via Gradient Flow Extinction.

Leon Bungert, Martin Burger, Daniel Tenbrinck

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2019

2018

A Graph Framework for Manifold-Valued Data.

Ronny Bergmann, Daniel Tenbrinck

SIAM J. Imaging Sci., 2018

2017

Nonlocal Inpainting of Manifold-Valued Data on Finite Weighted Graphs.

Ronny Bergmann, Daniel Tenbrinck

Proceedings of the Geometric Science of Information - Third International Conference, 2017

2015

On the p-Laplacian and ∞-Laplacian on Graphs with Applications in Image and Data Processing.

Abderrahim Elmoataz, Matthieu Toutain, Daniel Tenbrinck

SIAM J. Imaging Sci., 2015

Image segmentation with arbitrary noise models by solving minimal surface problems.

Daniel Tenbrinck, Xiaoyi Jiang

Pattern Recognit., 2015

Solving Minimal Surface Problems on Surfaces and Point Clouds.

Daniel Tenbrinck, François Lozes, Abderrahim Elmoataz

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2015

2014

Automatic classification of left ventricular wall segments in small animal ultrasound imaging.

Kathrin Ungru, Daniel Tenbrinck, Xiaoyi Jiang, Jörg Stypmann

Comput. Methods Programs Biomed., 2014

Registration of Noisy Images via Maximum A-Posteriori Estimation.

Sebastian Suhr, Daniel Tenbrinck, Martin Burger, Jan Modersitzki

Proceedings of the Biomedical Image Registration - 6th International Workshop, 2014

2013

Histogram-Based Optical Flow for Motion Estimation in Ultrasound Imaging.

Daniel Tenbrinck, Sönke Schmid, Xiaoyi Jiang, Klaus P. Schäfers, Jörg Stypmann

J. Math. Imaging Vis., 2013

A Variational Framework for Region-Based Segmentation Incorporating Physical Noise Models.

Alex Sawatzky, Daniel Tenbrinck, Xiaoyi Jiang, Martin Burger

J. Math. Imaging Vis., 2013

Discriminant Analysis Based Level Set Segmentation for Ultrasound Imaging.

Daniel Tenbrinck, Xiaoyi Jiang

Proceedings of the Computer Analysis of Images and Patterns, 2013

Region Based Contour Detection by Dynamic Programming.

Xiaoyi Jiang, Daniel Tenbrinck

Proceedings of the Computer Analysis of Images and Patterns, 2013

Biomedical Imaging: A Computer Vision Perspective.

Xiaoyi Jiang, Mohammad Dawood, Fabian Gigengack, Benjamin Risse, Sönke Schmid, Daniel Tenbrinck, Klaus P. Schäfers

Proceedings of the Computer Analysis of Images and Patterns, 2013

Variational Methods for Medical Ultrasound Imaging.

Daniel Tenbrinck

PhD thesis, 2013

2012

Impact of Physical Noise Modeling on Image Segmentation in Echocardiography.

Daniel Tenbrinck, Alex Sawatzky, Xiaoyi Jiang, Martin Burger, Wladimir Haffner, Patrick Willems, Matthias Paul, Jörg Stypmann

Proceedings of the Eurographics Workshop on Visual Computing for Biomedicine, 2012

2011

Histogram-Based Optical Flow for Functional Imaging in Echocardiography.

Sönke Schmid, Daniel Tenbrinck, Xiaoyi Jiang, Klaus P. Schäfers, Klaus Tiemann, Jörg Stypmann

Proceedings of the Computer Analysis of Images and Patterns, 2011

2010

Motion correction in positron emission tomography considering partial volume effects in optical flow estimation.

Daniel Tenbrinck, Mohammad Dawood, Fabian Gigengack, Michael Fieseler, Xiaoyi Jiang, Klaus Schiifers

Proceedings of the 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2010