Multiscale Vascular Surface Model Generation From Medical Imaging Data Using Hierarchical Features. - Erik J. Bekkers; Charles A. Taylor (IEEE Trans. Medical Imaging, 2008)

A New Retinal Vessel Tracking Method Based on Orientation Scores - Erik J. Bekkers; Remco Duits; Bart M. ter Haar Romeny; Tos Berendschot (CoRR, 2012)

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 (EMMCVPR, 2014)

Optic Nerve Head Detection via Group Correlations in Multi-orientation Transforms. - Erik J. Bekkers; Remco Duits; Bart M. ter Haar Romeny (ICIAR (2), 2014)

Crossing-Preserving Multi-scale Vesselness. - Julius Hannink; Remco Duits; Erik J. Bekkers (MICCAI (2), 2014)

Vesselness via Multiple Scale Orientation Scores. - Julius Hannink; Remco Duits; Erik J. Bekkers (CoRR, 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)

Sub-Riemannian Fast Marching in SE(2). - Gonzalo Sanguinetti; Erik J. Bekkers; Remco Duits; Michiel H. J. Janssen; Alexey Mashtakov; Jean-Marie Mirebeau (CIARP, 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 (ICIAP (1), 2015)

Data-Driven Sub-Riemannian Geodesics in SE(2). - Erik J. Bekkers; Remco Duits; Alexey Mashtakov; Gonzalo R. Sanguinetti (SSVM, 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)

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 (ISBI, 2016)

Template Matching on the Roto-Translation Group. - Erik J. Bekkers; Marco Loog; Bart M. ter Haar Romeny; Remco Duits (CoRR, 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; et al. (Mach. Vis. Appl., 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)

Vessel Tracking via Sub-Riemannian Geodesics on the Projective Line Bundle. - Erik J. Bekkers; Remco Duits; Alexey Mashtakov; Yuri Sachkov (GSI, 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 (SSVM, 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)

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)

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)

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 (MICCAI (1), 2018)

Nilpotent Approximations of Sub-Riemannian Distances for Fast Perceptual Grouping of Blood Vessels in 2D and 3D. - Erik J. Bekkers; Da Chen 002; Jorg M. Portegies (J. Math. Imaging Vis., 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)

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)

Reconnection of Interrupted Curvilinear Structures via Cortically Inspired Completion for Ophthalmologic Images. - Jiong Zhang; Erik J. Bekkers; Da Chen 002; 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)

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)

B-Spline CNNs on Lie groups. - Erik J. Bekkers (ICLR, 2020)

Attentive Group Equivariant Convolutional Networks. - David W. Romero; Erik J. Bekkers; Jakub M. Tomczak; Mark Hoogendoorn (ICML, 2020)

Wavelet Networks: Scale Equivariant Learning From Raw Waveforms. - David W. Romero; Erik J. Bekkers; Jakub M. Tomczak; Mark Hoogendoorn (CoRR, 2020)

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 (SSVM, 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)

Towards Lightweight Controllable Audio Synthesis with Conditional Implicit Neural Representations. - Jan Zuiderveld; Marco Federici; Erik J. Bekkers (CoRR, 2021)

ChebLieNet: Invariant Spectral Graph NNs Turned Equivariant by Riemannian Geometry on Lie Groups. - Hugo Aguettaz; Erik J. Bekkers; Michaël Defferrard (CoRR, 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)

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; et al. (CinC, 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; et al. (CinC, 2022)

Preface. - Erik J. Bekkers; Jelmer M. Wolterink; Angelica I. Avilés-Rivero (GeoMedIA, 2022)

Group Convolutional Neural Networks for DWI Segmentation. - Renfei Liu; François Lauze; Erik J. Bekkers; Kenny Erleben; Sune Darkner (GeoMedIA, 2022)

Geometric and Physical Quantities improve E(3) Equivariant Message Passing. - Johannes Brandstetter; Rob Hesselink; Elise van der Pol; Erik J. Bekkers; Max Welling (ICLR, 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 (ICLR, 2022)

CKConv: Continuous Kernel Convolution For Sequential Data. - David W. Romero; Anna Kuzina; Erik J. Bekkers; Jakub Mikolaj Tomczak; Mark Hoogendoorn (ICLR, 2022)

Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups. - David M. Knigge; David W. Romero; Erik J. Bekkers (ICML, 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)

Continuous Kendall Shape Variational Autoencoders. - Sharvaree P. Vadgama; Jakub M. Tomczak; Erik J. Bekkers (GSI (1), 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 (ICCV (Workshops), 2023)

Geometric Contrastive Learning. - Yeskendir Koishekenov; Sharvaree P. Vadgama; Riccardo Valperga; Erik J. Bekkers (ICCV (Workshops), 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 (ICLR, 2023)

E(n) Equivariant Message Passing Simplicial Networks. - Floor Eijkelboom; Rob Hesselink; Erik J. Bekkers (ICML, 2023)

Regular SE(3) Group Convolutions for Volumetric Medical Image Analysis. - Thijs P. Kuipers; Erik J. Bekkers (MICCAI (3), 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 (CaPTion@MICCAI, 2023)

Latent Field Discovery in Interacting Dynamical Systems with Neural Fields. - Miltiadis Kofinas; Erik J. Bekkers; Naveen Shankar Nagaraja; Efstratios Gavves (NeurIPS, 2023)

Can strong structural encoding reduce the importance of Message Passing? - Floor Eijkelboom; Erik J. Bekkers; Michael M. Bronstein; Francesco Di Giovanni (TAG-ML, 2023)

Learned Gridification for Efficient Point Cloud Processing. - Putri A. van der Linden; David W. Romero; Erik J. Bekkers (TAG-ML, 2023)

On genuine invariance learning without weight-tying. - Artem Moskalev; Anna Sepliarskaia; Erik J. Bekkers; Arnold W. M. Smeulders (TAG-ML, 2023)

An Exploration of Conditioning Methods in Graph Neural Networks. - Yeskendir Koishekenov; Erik J. Bekkers (CoRR, 2023)

PDE-Based Group Equivariant Convolutional Neural Networks. - Bart M. N. Smets; Jim Portegies; Erik J. Bekkers; Remco Duits (J. Math. Imaging Vis., 2023)

Electrostatic field dataset - Latent Field Discovery in Interacting Dynamical Systems with Neural Fields. - Miltiadis Kofinas; Erik Johannes Bekkers; Naveen Shankar Nagaraja; Efstratios Gavves (Zenodo, 2023)

Dynamic gravitational field dataset - Latent Field Discovery in Interacting Dynamical Systems with Neural Fields. - Miltiadis Kofinas; Erik Johannes Bekkers; Naveen Shankar Nagaraja; Efstratios Gavves (Zenodo, 2023)

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 (ICLR, 2024)

Uncertainty-aware retinal layer segmentation in OCT through probabilistic signed distance functions. - Mohammad Mohaiminul Islam; Coen de Vente; Bart Liefers; Caroline Klaver; Erik J. Bekkers; Clara I. Sánchez (MIDL, 2024)

Generating Cerebral Vessel Trees of Acute Ischemic Stroke Patients using Conditional Set-Diffusion. - Thijs P. Kuipers; Praneeta Konduri; Henk A. Marquering; Erik J. Bekkers (MIDL, 2024)

Space-Time Continuous PDE Forecasting using Equivariant Neural Fields. - David M. Knigge; David R. Wessels; Riccardo Valperga; Samuele Papa; Jan-Jakob Sonke; Erik J. Bekkers; Efstratios Gavves (NeurIPS, 2024)

Learning symmetries via weight-sharing with doubly stochastic tensors. - Putri A. van der Linden; Alejandro García-Castellanos; Sharvaree P. Vadgama; Thijs P. Kuipers; Erik J. Bekkers (NeurIPS, 2024)

E(n) Equivariant Message Passing Cellular Networks. - Veljko Kovac; Erik J. Bekkers; Pietro Liò; Floor Eijkelboom (CoRR, 2024)

The Hidden Pitfalls of the Cosine Similarity Loss. - Andrew Draganov; Sharvaree P. Vadgama; Erik J. Bekkers (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; et al. (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)

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)

Pullback Flow Matching on Data Manifolds. - Friso de Kruiff; Erik J. Bekkers; Ozan Öktem; Carola-Bibiane Schönlieb; Willem Diepeveen (CoRR, 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)

Grounding Continuous Representations in Geometry: Equivariant Neural Fields. - David R. Wessels; David M. Knigge; Riccardo Valperga; Samuele Papa; Sharvaree P. Vadgama; Efstratios Gavves; Erik J. Bekkers (ICLR, 2025)

CP2: Leveraging Geometry for Conformal Prediction via Canonicalization. - Putri A. van der Linden; Alexander Timans; Erik J. Bekkers (UAI, 2025)

SE(3) group convolutional neural networks and a study on group convolutions and equivariance for DWI segmentation. - Renfei Liu; François Lauze; Erik J. Bekkers; Sune Darkner; Kenny Erleben (Frontiers Artif. Intell., 2025)

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. - Xuan Zhang; Limei Wang; Jacob Helwig; Youzhi Luo; Cong Fu 003; Yaochen Xie; Meng Liu 015; Yuchao Lin; Zhao Xu 005; Keqiang Yan; Keir Adams; Maurice Weiler; et al. (Found. Trends Mach. Learn., 2025)

On the Utility of Equivariance and Symmetry Breaking in Deep Learning Architectures on Point Clouds. - Sharvaree P. Vadgama; Mohammad Mohaiminul Islam; Domas Buracus; Christian Shewmake; Erik J. Bekkers (CoRR, 2025)

On the Importance of Embedding Norms in Self-Supervised Learning. - Andrew Draganov; Sharvaree P. Vadgama; Sebastian Damrich; Jan Niklas Böhm; Lucas Maes; Dmitry Kobak; Erik J. Bekkers (CoRR, 2025)

Towards Variational Flow Matching on General Geometries. - Olga Zaghen; Floor Eijkelboom; Alison Pouplin; Erik J. Bekkers (CoRR, 2025)

Orientation Scores should be a Piece of Cake. - Finn M. Sherry; Chase van de Geijn; Erik J. Bekkers; Remco Duits (CoRR, 2025)

Clifford Group Equivariant Diffusion Models for 3D Molecular Generation. - Cong Liu; Sharvaree Vadgama; David Ruhe; Erik J. Bekkers; Patrick Forré (CoRR, 2025)

AdS-GNN - a Conformally Equivariant Graph Neural Network. - Maksim Zhdanov 001; Nabil Iqbal; Erik J. Bekkers; Patrick Forré (CoRR, 2025)

Equivariant Eikonal Neural Networks: Grid-Free, Scalable Travel-Time Prediction on Homogeneous Spaces. - Alejandro García-Castellanos; David R. Wessels; Nicky J. van den Berg; Remco Duits; Daniël M. Pelt; Erik J. Bekkers (CoRR, 2025)

Controlled Generation with Equivariant Variational Flow Matching. - Floor Eijkelboom; Heiko Zimmermann; Sharvaree Vadgama; Erik J. Bekkers; Max Welling; Christian A. Naesseth; Jan-Willem van de Meent (CoRR, 2025)

On Equivariant Model Selection through the Lens of Uncertainty. - Putri A. van der Linden; Alexander Timans; Dharmesh Tailor; Erik J. Bekkers (CoRR, 2025)