Daniel Tenbrinck

Orcid: 0000-0002-4788-9332

According to our database1, Daniel Tenbrinck authored at least 30 papers between 2010 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

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Bibliography

2024
Hypergraph p-Laplacians and Scale Spaces.
J. Math. Imaging Vis., August, 2024

The Infinity Laplacian Eigenvalue Problem: Reformulation and a Numerical Scheme.
J. Sci. Comput., February, 2024

2023
Resolution-Invariant Image Classification Based on Fourier Neural Operators.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2023

Hypergraph p-Laplacians, Scale Spaces, and Information Flow in Networks.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2023

2022
A Bregman Learning Framework for Sparse Neural Networks.
J. Mach. Learn. Res., 2022

2021
Fenchel Duality Theory and a Primal-Dual Algorithm on Riemannian Manifolds.
Found. Comput. Math., 2021

Neural Architecture Search via Bregman Iterations.
CoRR, 2021

Identifying untrustworthy predictions in neural networks by geometric gradient analysis.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

CLIP: Cheap Lipschitz Training of Neural Networks.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2021

Dynamically Sampled Nonlocal Gradients for Stronger Adversarial Attacks.
Proceedings of the International Joint Conference on Neural Networks, 2021

2020
Sampled Nonlocal Gradients for Stronger Adversarial Attacks.
CoRR, 2020

2019
Fenchel Duality for Convex Optimization and a Primal Dual Algorithm on Riemannian Manifolds.
CoRR, 2019

Variational Graph Methods for Efficient Point Cloud Sparsification.
CoRR, 2019

Computing Nonlinear Eigenfunctions via Gradient Flow Extinction.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2019

2018
A Graph Framework for Manifold-Valued Data.
SIAM J. Imaging Sci., 2018

2017
Nonlocal Inpainting of Manifold-Valued Data on Finite Weighted Graphs.
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.
SIAM J. Imaging Sci., 2015

Image segmentation with arbitrary noise models by solving minimal surface problems.
Pattern Recognit., 2015

Solving Minimal Surface Problems on Surfaces and Point Clouds.
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.
Comput. Methods Programs Biomed., 2014

Registration of Noisy Images via Maximum A-Posteriori Estimation.
Proceedings of the Biomedical Image Registration - 6th International Workshop, 2014

2013
Histogram-Based Optical Flow for Motion Estimation in Ultrasound Imaging.
J. Math. Imaging Vis., 2013

A Variational Framework for Region-Based Segmentation Incorporating Physical Noise Models.
J. Math. Imaging Vis., 2013

Discriminant Analysis Based Level Set Segmentation for Ultrasound Imaging.
Proceedings of the Computer Analysis of Images and Patterns, 2013

Region Based Contour Detection by Dynamic Programming.
Proceedings of the Computer Analysis of Images and Patterns, 2013

Biomedical Imaging: A Computer Vision Perspective.
Proceedings of the Computer Analysis of Images and Patterns, 2013

Variational Methods for Medical Ultrasound Imaging.
PhD thesis, 2013

2012
Impact of Physical Noise Modeling on Image Segmentation in Echocardiography.
Proceedings of the Eurographics Workshop on Visual Computing for Biomedicine, 2012

2011
Histogram-Based Optical Flow for Functional Imaging in Echocardiography.
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.
Proceedings of the 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2010


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