Erik J. Bekkers

Orcid: 0000-0003-4418-2160

Affiliations:
  • University of Amsterdam, Machine Learning Lab (AMLab), The Netherlands
  • Technical University Eindhoven (TU/e), Department of Applied Mathematics, The Netherlands (PhD 2017)


According to our database1, Erik J. Bekkers authored at least 58 papers between 2008 and 2023.

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Bibliography

2023
PDE-Based Group Equivariant Convolutional Neural Networks.
J. Math. Imaging Vis., January, 2023

Fast, Expressive SE(n) Equivariant Networks through Weight-Sharing in Position-Orientation Space.
CoRR, 2023

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems.
CoRR, 2023

An Exploration of Conditioning Methods in Graph Neural Networks.
CoRR, 2023

On genuine invariance learning without weight-tying.
Proceedings of the Topological, 2023

Learned Gridification for Efficient Point Cloud Processing.
Proceedings of the Topological, 2023

Can strong structural encoding reduce the importance of Message Passing?
Proceedings of the Topological, 2023

Latent Field Discovery in Interacting Dynamical Systems with Neural Fields.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Modeling Barrett's Esophagus Progression Using Geometric Variational Autoencoders.
Proceedings of the Cancer Prevention Through Early Detection, 2023

Regular SE(3) Group Convolutions for Volumetric Medical Image Analysis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

E(n) Equivariant Message Passing Simplicial Networks.
Proceedings of the International Conference on Machine Learning, 2023

Modelling Long Range Dependencies in $N$D: From Task-Specific to a General Purpose CNN.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Geometric Contrastive Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Geometric Superpixel Representations for Efficient Image Classification with Graph Neural Networks.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Continuous Kendall Shape Variational Autoencoders.
Proceedings of the Geometric Science of Information - 6th International Conference, 2023

2022
Towards a General Purpose CNN for Long Range Dependencies in ND.
CoRR, 2022

Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups.
Proceedings of the International Conference on Machine Learning, 2022

CKConv: Continuous Kernel Convolution For Sequential Data.
Proceedings of the Tenth International Conference on Learning Representations, 2022

FlexConv: Continuous Kernel Convolutions With Differentiable Kernel Sizes.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Geometric and Physical Quantities improve E(3) Equivariant Message Passing.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Group Convolutional Neural Networks for DWI Segmentation.
Proceedings of the Geometric Deep Learning in Medical Image Analysis, 2022

Preface.
Proceedings of the Geometric Deep Learning in Medical Image Analysis, 2022

Deep Learning for Ventricular Arrhythmia Prediction Using Fibrosis Segmentations on Cardiac MRI Data.
Proceedings of the Computing in Cardiology, 2022

Weakly-Supervised Deep Learning for Left Ventricle Fibrosis Segmentation in Cardiac MRI Using Image-Level Labels.
Proceedings of the Computing in Cardiology, 2022

2021
Roto-translation equivariant convolutional networks: Application to histopathology image analysis.
Medical Image Anal., 2021

ChebLieNet: Invariant Spectral Graph NNs Turned Equivariant by Riemannian Geometry on Lie Groups.
CoRR, 2021

Towards Lightweight Controllable Audio Synthesis with Conditional Implicit Neural Representations.
CoRR, 2021

Interpretable ECG classification via a query-based latent space traversal (qLST).
CoRR, 2021

Equivariant Deep Learning via Morphological and Linear Scale Space PDEs on the Space of Positions and Orientations.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2021

2020
Wavelet Networks: Scale Equivariant Learning From Raw Waveforms.
CoRR, 2020

Attentive Group Equivariant Convolutional Networks.
Proceedings of the 37th International Conference on Machine Learning, 2020

B-Spline CNNs on Lie groups.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Fourier Transform on the Homogeneous Space of 3D Positions and Orientations for Exact Solutions to Linear PDEs.
Entropy, 2019

2018
Reconnection of Interrupted Curvilinear Structures via Cortically Inspired Completion for Ophthalmologic Images.
IEEE Trans. Biomed. Eng., 2018

Template Matching via Densities on the Roto-Translation Group.
IEEE Trans. Pattern Anal. Mach. Intell., 2018

Design and Processing of Invertible Orientation Scores of 3D Images.
J. Math. Imaging Vis., 2018

Nilpotent Approximations of Sub-Riemannian Distances for Fast Perceptual Grouping of Blood Vessels in 2D and 3D.
J. Math. Imaging Vis., 2018

Roto-Translation Covariant Convolutional Networks for Medical Image Analysis.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

2017
Retinal vessel delineation using a brain-inspired wavelet transform and random forest.
Pattern Recognit., 2017

Tracking of Lines in Spherical Images via Sub-Riemannian Geodesics in SO(3).
J. Math. Imaging Vis., 2017

Design and Processing of Invertible Orientation Scores of 3D Images for Enhancement of Complex Vasculature.
CoRR, 2017

The Hessian of Axially Symmetric Functions on SE(3) and Application in 3D Image Analysis.
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2017

Vessel Tracking via Sub-Riemannian Geodesics on the Projective Line Bundle.
Proceedings of the Geometric Science of Information - Third International Conference, 2017

2016
Robust Retinal Vessel Segmentation via Locally Adaptive Derivative Frames in Orientation Scores.
IEEE Trans. Medical Imaging, 2016

Brain-inspired algorithms for retinal image analysis.
Mach. Vis. Appl., 2016

Template Matching on the Roto-Translation Group.
CoRR, 2016

Automatic detection of vascular bifurcations and crossings in retinal images using orientation scores.
Proceedings of the 13th IEEE International Symposium on Biomedical Imaging, 2016

2015
A PDE Approach to Data-Driven Sub-Riemannian Geodesics in SE(2).
SIAM J. Imaging Sci., 2015

Data-Driven Sub-Riemannian Geodesics in SE(2).
Proceedings of the Scale Space and Variational Methods in Computer Vision, 2015

Robust and Fast Vessel Segmentation via Gaussian Derivatives in Orientation Scores.
Proceedings of the Image Analysis and Processing - ICIAP 2015, 2015

Sub-Riemannian Fast Marching in SE(2).
Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2015

2014
A Multi-Orientation Analysis Approach to Retinal Vessel Tracking.
J. Math. Imaging Vis., 2014

Vesselness via Multiple Scale Orientation Scores.
CoRR, 2014

Crossing-Preserving Multi-scale Vesselness.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014

Optic Nerve Head Detection via Group Correlations in Multi-orientation Transforms.
Proceedings of the Image Analysis and Recognition - 11th International Conference, 2014

Training of Templates for Object Recognition in Invertible Orientation Scores: Application to Optic Nerve Head Detection in Retinal Images.
Proceedings of the Energy Minimization Methods in Computer Vision and Pattern Recognition, 2014

2012
A New Retinal Vessel Tracking Method Based on Orientation Scores
CoRR, 2012

2008
Multiscale Vascular Surface Model Generation From Medical Imaging Data Using Hierarchical Features.
IEEE Trans. Medical Imaging, 2008


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