Erik J. Bekkers

According to our database, Erik J. Bekkers authored at least 66 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Wavelet Networks: Scale-Translation Equivariant Learning From Raw Time-Series.

David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn

Trans. Mach. Learn. Res., 2024

The NGT200 Dataset: Geometric Multi-View Isolated Sign Recognition.

Oline Ranum, David R. Wessels, Gomer Otterspeer, Erik J. Bekkers, Floris Roelofsen, Jari I. Andersen

CoRR, 2024

HyperSteiner: Computing Heuristic Hyperbolic Steiner Minimal Trees.

Alejandro García-Castellanos, Aniss Aiman Medbouhi, Giovanni Luca Marchetti, Erik J. Bekkers, Danica Kragic

CoRR, 2024

ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain.

Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna, Federica Baccini, Mathilde Papillon, Miquel Ferriol Galmés, Mustafa Hajij, Theodore Papamarkou, Maria Sofia Bucarelli, Olga Zaghen, Johan Mathe, Audun Myers, Scott Mahan, Hansen Lillemark, Sharvaree P. Vadgama, Erik J. Bekkers, Tim Doster, Tegan Emerson, Henry Kvinge, Katrina Agate, Nesreen K. Ahmed, Pengfei Bai, Michael Banf, Claudio Battiloro, Maxim Beketov, Paul Bogdan, Martin Carrasco, Andrea Cavallo, Yun Young Choi, George Dasoulas, Matous Elphick, Giordan Escalona, Dominik Filipiak, Halley Fritze, Thomas Gebhart, Manel Gil-Sorribes, Salvish Goomanee, Victor Guallar, Liliya Imasheva, Andrei Irimia, Hongwei Jin, Graham Johnson, Nikos Kanakaris, Boshko Koloski, Veljko Kovac, Manuel Lecha, Minho Lee, Pierrick Leroy, Theodore Long, German Magai, Alvaro Martinez, Marissa Masden, Sebastian Meznar, Bertran Miquel-Oliver, Alexis Molina, Alexander Nikitin, Marco Nurisso, Matt Piekenbrock, Yu Qin, Patryk Rygiel, Alessandro Salatiello, Max Schattauer, Pavel Snopov, Julian Suk, Valentina Sánchez, Mauricio Tec, Francesco Vaccarino, Jonas Verhellen, Frédéric Wantiez, Alexander Weers, Patrik Zajec, Blaz Skrlj, Nina Miolane

CoRR, 2024

The Hidden Pitfalls of the Cosine Similarity Loss.

Andrew Draganov, Sharvaree P. Vadgama, Erik J. Bekkers

CoRR, 2024

Space-Time Continuous PDE Forecasting using Equivariant Neural Fields.

David M. Knigge, David R. Wessels, Riccardo Valperga, Samuele Papa, Jan-Jakob Sonke, Efstratios Gavves, Erik J. Bekkers

CoRR, 2024

Grounding Continuous Representations in Geometry: Equivariant Neural Fields.

David R. Wessels, David M. Knigge, Samuele Papa, Riccardo Valperga, Sharvaree P. Vadgama, Efstratios Gavves, Erik J. Bekkers

CoRR, 2024

E(n) Equivariant Message Passing Cellular Networks.

Veljko Kovac, Erik J. Bekkers, Pietro Liò, Floor Eijkelboom

CoRR, 2024

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

Erik J. Bekkers, Sharvaree P. Vadgama, Rob Hesselink, Putri A. van der Linden, David W. Romero

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

PDE-Based Group Equivariant Convolutional Neural Networks.

Bart M. N. Smets, Jim Portegies, Erik J. Bekkers, Remco Duits

J. Math. Imaging Vis., January, 2023

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

Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Haiyang Yu, Yuqing Xie, Xiang Fu, Alex Strasser, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji

CoRR, 2023

An Exploration of Conditioning Methods in Graph Neural Networks.

Yeskendir Koishekenov, Erik J. Bekkers

CoRR, 2023

On genuine invariance learning without weight-tying.

Artem Moskalev, Anna Sepliarskaia, Erik J. Bekkers, Arnold W. M. Smeulders

Proceedings of the Topological, 2023

Learned Gridification for Efficient Point Cloud Processing.

Putri A. van der Linden, David W. Romero, Erik J. Bekkers

Proceedings of the Topological, 2023

Can strong structural encoding reduce the importance of Message Passing?

Floor Eijkelboom, Erik J. Bekkers, Michael M. Bronstein, Francesco Di Giovanni

Proceedings of the Topological, 2023

Latent Field Discovery in Interacting Dynamical Systems with Neural Fields.

Miltiadis Kofinas, Erik J. Bekkers, Naveen Shankar Nagaraja, Efstratios Gavves

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.

Vivien van Veldhuizen, Sharvaree P. Vadgama, Onno J. de Boer, Sybren L. Meijer, Erik J. Bekkers

Proceedings of the Cancer Prevention Through Early Detection, 2023

Regular SE(3) Group Convolutions for Volumetric Medical Image Analysis.

Thijs P. Kuipers, Erik J. Bekkers

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

E(n) Equivariant Message Passing Simplicial Networks.

Floor Eijkelboom, Rob Hesselink, Erik J. Bekkers

Proceedings of the International Conference on Machine Learning, 2023

Modelling Long Range Dependencies in $N$D: From Task-Specific to a General Purpose CNN.

David M. Knigge, David W. Romero, Albert Gu, Efstratios Gavves, Erik J. Bekkers, Jakub Mikolaj Tomczak, Mark Hoogendoorn, Jan-Jakob Sonke

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Geometric Contrastive Learning.

Yeskendir Koishekenov, Sharvaree P. Vadgama, Riccardo Valperga, Erik J. Bekkers

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Geometric Superpixel Representations for Efficient Image Classification with Graph Neural Networks.

Radu A. Cosma, Lukas Knobel, Putri A. van der Linden, David M. Knigge, Erik J. Bekkers

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Continuous Kendall Shape Variational Autoencoders.

Sharvaree P. Vadgama, Jakub M. Tomczak, Erik J. Bekkers

Proceedings of the Geometric Science of Information - 6th International Conference, 2023

2022

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

David W. Romero, David M. Knigge, Albert Gu, Erik J. Bekkers, Efstratios Gavves, Jakub M. Tomczak, Mark Hoogendoorn

CoRR, 2022

Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups.

David M. Knigge, David W. Romero, Erik J. Bekkers

Proceedings of the International Conference on Machine Learning, 2022

CKConv: Continuous Kernel Convolution For Sequential Data.

David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub Mikolaj Tomczak, Mark Hoogendoorn

Proceedings of the Tenth International Conference on Learning Representations, 2022

FlexConv: Continuous Kernel Convolutions With Differentiable Kernel Sizes.

David W. Romero, Robert-Jan Bruintjes, Jakub Mikolaj Tomczak, Erik J. Bekkers, Mark Hoogendoorn, Jan van Gemert

Proceedings of the Tenth International Conference on Learning Representations, 2022

Geometric and Physical Quantities improve E(3) Equivariant Message Passing.

Johannes Brandstetter, Rob Hesselink, Elise van der Pol, Erik J. Bekkers, Max Welling

Proceedings of the Tenth International Conference on Learning Representations, 2022

Group Convolutional Neural Networks for DWI Segmentation.

Renfei Liu, François Lauze, Erik J. Bekkers, Kenny Erleben, Sune Darkner

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

Preface.

Erik J. Bekkers, Jelmer M. Wolterink, Angelica I. Avilés-Rivero

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

Deep Learning for Ventricular Arrhythmia Prediction Using Fibrosis Segmentations on Cardiac MRI Data.

Florence E. van Lieshout, Roel C. Klein, Maarten Z. Kolk, Kylian van Geijtenbeek, Romy Vos, Samuel Ruipérez-Campillo, Ruibin Feng, Brototo Deb, Prasanth Ganesan, Reinoud Knops, Ivana Isgum, Sanjiv M. Narayan, Erik J. Bekkers, Bob D. de Vos, Fleur V. Y. Tjong

Proceedings of the Computing in Cardiology, 2022

Weakly-Supervised Deep Learning for Left Ventricle Fibrosis Segmentation in Cardiac MRI Using Image-Level Labels.

Roel C. Klein, Florence E. van Lieshout, Maarten Z. Kolk, Kylian van Geijtenbeek, Romy Vos, Samuel Ruipérez-Campillo, Ruibin Feng, Brototo Deb, Prasanth Ganesan, Reinoud Knops, Ivana Isgum, Sanjiv M. Narayan, Erik J. Bekkers, Bob D. de Vos, Fleur V. Y. Tjong

Proceedings of the Computing in Cardiology, 2022

2021

Roto-translation equivariant convolutional networks: Application to histopathology image analysis.

Maxime W. Lafarge, Erik J. Bekkers, Josien P. W. Pluim, Remco Duits, Mitko Veta

Medical Image Anal., 2021

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

Hugo Aguettaz, Erik J. Bekkers, Michaël Defferrard

CoRR, 2021

Towards Lightweight Controllable Audio Synthesis with Conditional Implicit Neural Representations.

Jan Zuiderveld, Marco Federici, Erik J. Bekkers

CoRR, 2021

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

Melle B. Vessies, Sharvaree P. Vadgama, Rutger R. van de Leur, Pieter A. F. M. Doevendans, Rutger J. Hassink, Erik J. Bekkers, René van Es

CoRR, 2021

Equivariant Deep Learning via Morphological and Linear Scale Space PDEs on the Space of Positions and Orientations.

Remco Duits, Bart M. N. Smets, Erik J. Bekkers, Jim Portegies

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

2020

Wavelet Networks: Scale Equivariant Learning From Raw Waveforms.

David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn

CoRR, 2020

Attentive Group Equivariant Convolutional Networks.

David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn

Proceedings of the 37th International Conference on Machine Learning, 2020

B-Spline CNNs on Lie groups.

Erik J. Bekkers

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.

Remco Duits, Erik J. Bekkers, Alexey Mashtakov

Entropy, 2019

2018

Reconnection of Interrupted Curvilinear Structures via Cortically Inspired Completion for Ophthalmologic Images.

Jiong Zhang, Erik J. Bekkers, Da Chen, Tos T. J. M. Berendschot, Jan Schouten, Josien P. W. Pluim, Yonggang Shi, Behdad Dashtbozorg, Bart M. ter Haar Romeny

IEEE Trans. Biomed. Eng., 2018

Template Matching via Densities on the Roto-Translation Group.

Erik J. Bekkers, Marco Loog, Bart M. ter Haar Romeny, Remco Duits

IEEE Trans. Pattern Anal. Mach. Intell., 2018

Design and Processing of Invertible Orientation Scores of 3D Images.

Michiel Janssen, A. J. E. M. Janssen, Erik J. Bekkers, Javier Oliván Bescós, Remco Duits

J. Math. Imaging Vis., 2018

Nilpotent Approximations of Sub-Riemannian Distances for Fast Perceptual Grouping of Blood Vessels in 2D and 3D.

Erik J. Bekkers, Da Chen, Jorg M. Portegies

J. Math. Imaging Vis., 2018

Roto-Translation Covariant Convolutional Networks for Medical Image Analysis.

Erik J. Bekkers, Maxime W. Lafarge, Mitko Veta, Koen A. J. Eppenhof, Josien P. W. Pluim, Remco Duits

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.

Jiong Zhang, Yuan Chen, Erik J. Bekkers, Meili Wang, Behdad Dashtbozorg, Bart M. ter Haar Romeny

Pattern Recognit., 2017

Tracking of Lines in Spherical Images via Sub-Riemannian Geodesics in SO(3).

Alexey Mashtakov, Remco Duits, Yuri Sachkov, Erik J. Bekkers, Ivan Beschastnyi

J. Math. Imaging Vis., 2017

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

Michiel H. J. Janssen, A. J. E. M. Janssen, Erik J. Bekkers, Javier Oliván Bescós, Remco Duits

CoRR, 2017

The Hessian of Axially Symmetric Functions on SE(3) and Application in 3D Image Analysis.

Michiel H. J. Janssen, Tom C. J. Dela Haije, Frank C. Martin, Erik J. Bekkers, Remco Duits

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2017

Vessel Tracking via Sub-Riemannian Geodesics on the Projective Line Bundle.

Erik J. Bekkers, Remco Duits, Alexey Mashtakov, Yuri Sachkov

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

2016

Robust Retinal Vessel Segmentation via Locally Adaptive Derivative Frames in Orientation Scores.

Jiong Zhang, Behdad Dashtbozorg, Erik J. Bekkers, Josien P. W. Pluim, Remco Duits, Bart M. ter Haar Romeny

IEEE Trans. Medical Imaging, 2016

Brain-inspired algorithms for retinal image analysis.

Bart M. ter Haar Romeny, Erik J. Bekkers, Jiong Zhang, Samaneh Abbasi-Sureshjani, Fan Huang, Remco Duits, Behdad Dashtbozorg, Tos Berendschot, Iris Smit-Ockeloen, Koen A. J. Eppenhof, Jinghan Feng, Julius Hannink, Jan Schouten, Mengmeng Tong, Hanhui Wu, Han J. W. van Triest, Shanshan Zhu, Dali Chen, Wei He, Ling Xu, Ping Han, Yan Kang

Mach. Vis. Appl., 2016

Template Matching on the Roto-Translation Group.

Erik J. Bekkers, Marco Loog, Bart M. ter Haar Romeny, Remco Duits

CoRR, 2016

Automatic detection of vascular bifurcations and crossings in retinal images using orientation scores.

Samaneh Abbasi-Sureshjani, Iris Smit-Ockeloen, Erik J. Bekkers, Behdad Dashtbozorg, Bart M. ter Haar Romeny

Proceedings of the 13th IEEE International Symposium on Biomedical Imaging, 2016

2015

A PDE Approach to Data-Driven Sub-Riemannian Geodesics in SE(2).

Erik J. Bekkers, Remco Duits, Alexey Mashtakov, Gonzalo R. Sanguinetti

SIAM J. Imaging Sci., 2015

Data-Driven Sub-Riemannian Geodesics in SE(2).

Erik J. Bekkers, Remco Duits, Alexey Mashtakov, Gonzalo R. Sanguinetti

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

Robust and Fast Vessel Segmentation via Gaussian Derivatives in Orientation Scores.

Jiong Zhang, Erik J. Bekkers, Samaneh Abbasi-Sureshjani, Behdad Dashtbozorg, Bart M. ter Haar Romeny

Proceedings of the Image Analysis and Processing - ICIAP 2015, 2015

Sub-Riemannian Fast Marching in SE(2).

Gonzalo Sanguinetti, Erik J. Bekkers, Remco Duits, Michiel H. J. Janssen, Alexey Mashtakov, Jean-Marie Mirebeau

Proceedings of the Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, 2015

2014

A Multi-Orientation Analysis Approach to Retinal Vessel Tracking.

Erik J. Bekkers, Remco Duits, Tos Berendschot, Bart M. ter Haar Romeny

J. Math. Imaging Vis., 2014

Vesselness via Multiple Scale Orientation Scores.

Julius Hannink, Remco Duits, Erik J. Bekkers

CoRR, 2014

Crossing-Preserving Multi-scale Vesselness.

Julius Hannink, Remco Duits, Erik J. Bekkers

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014

Optic Nerve Head Detection via Group Correlations in Multi-orientation Transforms.

Erik J. Bekkers, Remco Duits, Bart M. ter Haar Romeny

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.

Erik J. Bekkers, Remco Duits, Marco Loog

Proceedings of the Energy Minimization Methods in Computer Vision and Pattern Recognition, 2014

2012

A New Retinal Vessel Tracking Method Based on Orientation Scores

Erik J. Bekkers, Remco Duits, Bart M. ter Haar Romeny, Tos Berendschot

CoRR, 2012

2008

Multiscale Vascular Surface Model Generation From Medical Imaging Data Using Hierarchical Features.

Erik J. Bekkers, Charles A. Taylor

IEEE Trans. Medical Imaging, 2008