Christoph Brune

Orcid: 0000-0003-0145-5069

According to our database1, Christoph Brune authored at least 43 papers between 2009 and 2023.

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

Timeline

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Bibliography

2023
Embedding artificial intelligence in society: looking beyond the EU AI master plan using the culture cycle.
AI Soc., August, 2023

Learning a Sparse Representation of Barron Functions with the Inverse Scale Space Flow.
CoRR, 2023

SIRE: scale-invariant, rotation-equivariant estimation of artery orientations using graph neural networks.
CoRR, 2023

Trajectory Generation, Control, and Safety with Denoising Diffusion Probabilistic Models.
CoRR, 2023

Embeddings between Barron spaces with higher order activation functions.
CoRR, 2023

RSA-INR: Riemannian Shape Autoencoding via 4D Implicit Neural Representations.
CoRR, 2023

Uncertainty-Based Quality Assurance of Carotid Artery Wall Segmentation in Black-Blood MRI.
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2023

DFM-X: Augmentation by Leveraging Prior Knowledge of Shortcut Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

What do neural networks learn in image classification? A frequency shortcut perspective.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

SE(3) Symmetry Lets Graph Neural Networks Learn Arterial Velocity Estimation from Small Datasets.
Proceedings of the Functional Imaging and Modeling of the Heart, 2023

Implicit Neural Representations for Modeling of Abdominal Aortic Aneurysm Progression.
Proceedings of the Functional Imaging and Modeling of the Heart, 2023

Defocus Blur Synthesis and Deblurring via Interpolation and Extrapolation in Latent Space.
Proceedings of the Computer Analysis of Images and Patterns, 2023

Fourier Descriptor Loss and Polar Coordinate Transformation for Pericardium Segmentation.
Proceedings of the Computer Analysis of Images and Patterns, 2023

2022
Super-Resolved Microbubble Localization in Single-Channel Ultrasound RF Signals Using Deep Learning.
IEEE Trans. Medical Imaging, 2022

Discovering Efficient Periodic Behaviours in Mechanical Systems via Neural Approximators.
CoRR, 2022

Mesh Neural Networks for SE(3)-Equivariant Hemodynamics Estimation on the Artery Wall.
CoRR, 2022

Duality for Neural Networks through Reproducing Kernel Banach Spaces.
CoRR, 2022

Unsupervised Representation Learning in Deep Reinforcement Learning: A Review.
CoRR, 2022

Deep Kernel Learning of Dynamical Models from High-Dimensional Noisy Data.
CoRR, 2022

Going Off-Grid: Continuous Implicit Neural Representations for 3D Vascular Modeling.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers, 2022

Deep-learning-based carotid artery vessel wall segmentation in black-blood MRI using anatomical priors.
Proceedings of the Medical Imaging 2022: Image Processing, 2022

Implicit Neural Representations for Deformable Image Registration.
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

Self-supervised Learning Through Colorization for Microscopy Images.
Proceedings of the Image Analysis and Processing - ICIAP 2022, 2022

2021
Low-Dimensional State and Action Representation Learning with MDP Homomorphism Metrics.
CoRR, 2021

Learning normal form autoencoders for data-driven discovery of universal, parameter-dependent governing equations.
CoRR, 2021

Mesh Convolutional Neural Networks for Wall Shear Stress Estimation in 3D Artery Models.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge, 2021

Towards Autonomous Pipeline Inspection with Hierarchical Reinforcement Learning.
Proceedings of the Robot Intelligence Technology and Applications 6, 2021

Low Dimensional State Representation Learning with Robotics Priors in Continuous Action Spaces.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

2020
A Partially-Learned Algorithm for Joint Photo-acoustic Reconstruction and Segmentation.
IEEE Trans. Medical Imaging, 2020

Deep learning of circulating tumour cells.
Nat. Mach. Intell., 2020

Low Dimensional State Representation Learning with Reward-shaped Priors.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

2019
Learned SVD: solving inverse problems via hybrid autoencoding.
CoRR, 2019

2017
Multiscale Segmentation via Bregman Distances and Nonlinear Spectral Analysis.
SIAM J. Imaging Sci., 2017

Combining Contrast Invariant L1 Data Fidelities with Nonlinear Spectral Image Decomposition.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2017

2014
Optimal data collection for informative rankings expose well-connected graphs.
J. Mach. Learn. Res., 2014

2013
Higher-Order TV Methods - Enhancement via Bregman Iteration.
J. Sci. Comput., 2013

Enhanced statistical rankings via targeted data collection.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Optimal Data Collection for Improved Rankings Expose Well-Connected Graphs
CoRR, 2012

2011
Primal and Dual Bregman Methods with Application to Optical Nanoscopy.
Int. J. Comput. Vis., 2011

2010
A Continuity Equation Based Optical Flow Method for Cardiac Motion Correction in 3D PET Data.
Proceedings of the Medical Imaging and Augmented Reality - 5th International Workshop, 2010

2009
Detection of Intensity and Motion Edges within Optical Flow via Multidimensional Control.
SIAM J. Imaging Sci., 2009

Bregman-EM-TV Methods with Application to Optical Nanoscopy.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2009

Total Variation Processing of Images with Poisson Statistics.
Proceedings of the Computer Analysis of Images and Patterns, 13th International Conference, 2009


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