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Erik J. Bekkers
Erik Johannes Bekkers
Person information
- affiliation: University of Amsterdam, Machine Learning Lab (AMLab), The Netherlands
- affiliation (PhD 2017): Technical University Eindhoven (TU/e), Department of Applied Mathematics, The Netherlands
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2020 – today
- 2024
- [j15]David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn:
Wavelet Networks: Scale-Translation Equivariant Learning From Raw Time-Series. Trans. Mach. Learn. Res. 2024 (2024) - [c33]Erik J. Bekkers, Sharvaree P. Vadgama, Rob Hesselink, Putri A. van der Linden, David W. Romero:
Fast, Expressive SE(n) Equivariant Networks through Weight-Sharing in Position-Orientation Space. ICLR 2024 - [i35]Veljko Kovac, Erik J. Bekkers, Pietro Liò, Floor Eijkelboom:
E(n) Equivariant Message Passing Cellular Networks. CoRR abs/2406.03145 (2024) - [i34]David R. Wessels, David M. Knigge, Samuele Papa, Riccardo Valperga, Sharvaree P. Vadgama, Efstratios Gavves, Erik J. Bekkers:
Grounding Continuous Representations in Geometry: Equivariant Neural Fields. CoRR abs/2406.05753 (2024) - [i33]David M. Knigge, David R. Wessels, Riccardo Valperga, Samuele Papa, Jan-Jakob Sonke, Efstratios Gavves, Erik J. Bekkers:
Space-Time Continuous PDE Forecasting using Equivariant Neural Fields. CoRR abs/2406.06660 (2024) - [i32]Andrew Draganov, Sharvaree P. Vadgama, Erik J. Bekkers:
The Hidden Pitfalls of the Cosine Similarity Loss. CoRR abs/2406.16468 (2024) - [i31]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:
ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain. CoRR abs/2409.05211 (2024) - [i30]Alejandro García-Castellanos, Aniss Aiman Medbouhi, Giovanni Luca Marchetti, Erik J. Bekkers, Danica Kragic:
HyperSteiner: Computing Heuristic Hyperbolic Steiner Minimal Trees. CoRR abs/2409.05671 (2024) - [i29]Oline Ranum, David R. Wessels, Gomer Otterspeer, Erik J. Bekkers, Floris Roelofsen, Jari I. Andersen:
The NGT200 Dataset: Geometric Multi-View Isolated Sign Recognition. CoRR abs/2409.15284 (2024) - 2023
- [j14]Bart M. N. Smets
PDE-Based Group Equivariant Convolutional Neural Networks. J. Math. Imaging Vis. 65(1): 209-239 (2023) - [c32]Sharvaree P. Vadgama, Jakub M. Tomczak, Erik J. Bekkers:
Continuous Kendall Shape Variational Autoencoders. GSI (1) 2023: 73-81 - [c31]Radu A. Cosma, Lukas Knobel, Putri A. van der Linden, David M. Knigge, Erik J. Bekkers:
Geometric Superpixel Representations for Efficient Image Classification with Graph Neural Networks. ICCV (Workshops) 2023: 109-118 - [c30]Yeskendir Koishekenov, Sharvaree P. Vadgama, Riccardo Valperga, Erik J. Bekkers:
Geometric Contrastive Learning. ICCV (Workshops) 2023: 206-215 - [c29]David M. Knigge, David W. Romero, Albert Gu, Efstratios Gavves, Erik J. Bekkers
Modelling Long Range Dependencies in $N$D: From Task-Specific to a General Purpose CNN. ICLR 2023 - [c28]Floor Eijkelboom, Rob Hesselink, Erik J. Bekkers:
E(n) Equivariant Message Passing Simplicial Networks. ICML 2023: 9071-9081 - [c27]Vivien van Veldhuizen, Sharvaree P. Vadgama, Onno J. de Boer, Sybren L. Meijer, Erik J. Bekkers:
Modeling Barrett's Esophagus Progression Using Geometric Variational Autoencoders. CaPTion@MICCAI 2023: 132-142 - [c26]Thijs P. Kuipers
Regular SE(3) Group Convolutions for Volumetric Medical Image Analysis. MICCAI (3) 2023: 252-261 - [c25]Miltiadis Kofinas, Erik J. Bekkers, Naveen Shankar Nagaraja, Efstratios Gavves:
Latent Field Discovery in Interacting Dynamical Systems with Neural Fields. NeurIPS 2023 - [c24]Putri A. van der Linden, David W. Romero, Erik J. Bekkers:
Learned Gridification for Efficient Point Cloud Processing. TAG-ML 2023: 9-20 - [c23]Artem Moskalev, Anna Sepliarskaia, Erik J. Bekkers, Arnold W. M. Smeulders:
On genuine invariance learning without weight-tying. TAG-ML 2023: 218-227 - [c22]Floor Eijkelboom, Erik J. Bekkers, Michael M. Bronstein, Francesco Di Giovanni:
Can strong structural encoding reduce the importance of Message Passing? TAG-ML 2023: 278-288 - [i28]David M. Knigge, David W. Romero, Albert Gu, Efstratios Gavves, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn, Jan-Jakob Sonke:
Modelling Long Range Dependencies in N-D: From Task-Specific to a General Purpose CNN. CoRR abs/2301.10540 (2023) - [i27]Yeskendir Koishekenov, Erik J. Bekkers:
An Exploration of Conditioning Methods in Graph Neural Networks. CoRR abs/2305.01933 (2023) - [i26]Floor Eijkelboom, Rob Hesselink, Erik J. Bekkers:
E(n) Equivariant Message Passing Simplicial Networks. CoRR abs/2305.07100 (2023) - [i25]Thijs P. Kuipers, Erik J. Bekkers:
Regular SE(3) Group Convolutions for Volumetric Medical Image Analysis. CoRR abs/2306.13960 (2023) - [i24]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
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR abs/2307.08423 (2023) - [i23]Putri A. van der Linden, David W. Romero
Learned Gridification for Efficient Point Cloud Processing. CoRR abs/2307.14354 (2023) - [i22]Artem Moskalev, Anna Sepliarskaia, Erik J. Bekkers, Arnold W. M. Smeulders:
On genuine invariance learning without weight-tying. CoRR abs/2308.03904 (2023) - [i21]Erik J. Bekkers, Sharvaree P. Vadgama, Rob D. Hesselink, Putri A. van der Linden, David W. Romero
Fast, Expressive SE(n) Equivariant Networks through Weight-Sharing in Position-Orientation Space. CoRR abs/2310.02970 (2023) - [i20]Floor Eijkelboom, Erik J. Bekkers, Michael M. Bronstein, Francesco Di Giovanni:
Can strong structural encoding reduce the importance of Message Passing? CoRR abs/2310.15197 (2023) - [i19]Miltiadis Kofinas
Latent Field Discovery In Interacting Dynamical Systems With Neural Fields. CoRR abs/2310.20679 (2023) - 2022
- [c21]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
Weakly-Supervised Deep Learning for Left Ventricle Fibrosis Segmentation in Cardiac MRI Using Image-Level Labels. CinC 2022: 1-4 - [c20]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
Deep Learning for Ventricular Arrhythmia Prediction Using Fibrosis Segmentations on Cardiac MRI Data. CinC 2022: 1-4 - [c19]Erik J. Bekkers, Jelmer M. Wolterink, Angelica I. Avilés-Rivero:
Preface. GeoMedIA 2022: 1-2 - [c18]Renfei Liu, François Lauze, Erik J. Bekkers, Kenny Erleben, Sune Darkner:
Group Convolutional Neural Networks for DWI Segmentation. GeoMedIA 2022: 96-106 - [c17]Johannes Brandstetter, Rob Hesselink, Elise van der Pol, Erik J. Bekkers
Geometric and Physical Quantities improve E(3) Equivariant Message Passing. ICLR 2022 - [c16]David W. Romero, Robert-Jan Bruintjes, Jakub Mikolaj Tomczak, Erik J. Bekkers
FlexConv: Continuous Kernel Convolutions With Differentiable Kernel Sizes. ICLR 2022 - [c15]David W. Romero, Anna Kuzina, Erik J. Bekkers
CKConv: Continuous Kernel Convolution For Sequential Data. ICLR 2022 - [c14]David M. Knigge, David W. Romero, Erik J. Bekkers:
Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups. ICML 2022: 11359-11386 - [e1]Erik J. Bekkers, Jelmer M. Wolterink, Angelica I. Avilés-Rivero:
Geometric Deep Learning in Medical Image Analysis, 18 November 2022, Amsterdam, The Netherlands. Proceedings of Machine Learning Research 194, PMLR 2022 [contents] - [i18]David W. Romero, David M. Knigge, Albert Gu, Erik J. Bekkers, Efstratios Gavves, Jakub M. Tomczak, Mark Hoogendoorn:
Towards a General Purpose CNN for Long Range Dependencies in ND. CoRR abs/2206.03398 (2022) - 2021
- [j13]Maxime W. Lafarge
Roto-translation equivariant convolutional networks: Application to histopathology image analysis. Medical Image Anal. 68: 101849 (2021) - [c13]Remco Duits, Bart M. N. Smets, Erik J. Bekkers, Jim Portegies:
Equivariant Deep Learning via Morphological and Linear Scale Space PDEs on the Space of Positions and Orientations. SSVM 2021: 27-39 - [i17]David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn:
CKConv: Continuous Kernel Convolution For Sequential Data. CoRR abs/2102.02611 (2021) - [i16]Johannes Brandstetter, Rob Hesselink, Elise van der Pol, Erik J. Bekkers, Max Welling:
Geometric and Physical Quantities improve E(3) Equivariant Message Passing. CoRR abs/2110.02905 (2021) - [i15]David W. Romero, Robert-Jan Bruintjes, Jakub M. Tomczak, Erik J. Bekkers, Mark Hoogendoorn, Jan C. van Gemert:
FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes. CoRR abs/2110.08059 (2021) - [i14]David M. Knigge, David W. Romero, Erik J. Bekkers:
Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups. CoRR abs/2110.13059 (2021) - [i13]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:
Interpretable ECG classification via a query-based latent space traversal (qLST). CoRR abs/2111.07386 (2021) - [i12]Jan Zuiderveld, Marco Federici, Erik J. Bekkers:
Towards Lightweight Controllable Audio Synthesis with Conditional Implicit Neural Representations. CoRR abs/2111.08462 (2021) - [i11]Hugo Aguettaz, Erik J. Bekkers, Michaël Defferrard:
ChebLieNet: Invariant Spectral Graph NNs Turned Equivariant by Riemannian Geometry on Lie Groups. CoRR abs/2111.12139 (2021) - 2020
- [c12]Erik J. Bekkers:
B-Spline CNNs on Lie groups. ICLR 2020 - [c11]David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn:
Attentive Group Equivariant Convolutional Networks. ICML 2020: 8188-8199 - [i10]Bart M. N. Smets, Jim Portegies, Erik J. Bekkers, Remco Duits:
PDE-based Group Equivariant Convolutional Neural Networks. CoRR abs/2001.09046 (2020) - [i9]David W. Romero
Attentive Group Equivariant Convolutional Networks. CoRR abs/2002.03830 (2020) - [i8]Maxime W. Lafarge, Erik J. Bekkers, Josien P. W. Pluim, Remco Duits, Mitko Veta:
Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis. CoRR abs/2002.08725 (2020) - [i7]David W. Romero
Wavelet Networks: Scale Equivariant Learning From Raw Waveforms. CoRR abs/2006.05259 (2020)
2010 – 2019
- 2019
- [j12]Remco Duits
Fourier Transform on the Homogeneous Space of 3D Positions and Orientations for Exact Solutions to Linear PDEs. Entropy 21(1): 38 (2019) - [i6]Erik J. Bekkers:
B-Spline CNNs on Lie Groups. CoRR abs/1909.12057 (2019) - 2018
- [j11]Erik J. Bekkers
Nilpotent Approximations of Sub-Riemannian Distances for Fast Perceptual Grouping of Blood Vessels in 2D and 3D. J. Math. Imaging Vis. 60(6): 882-899 (2018) - [j10]Michiel Janssen, A. J. E. M. Janssen, Erik J. Bekkers
Design and Processing of Invertible Orientation Scores of 3D Images. J. Math. Imaging Vis. 60(9): 1427-1458 (2018) - [j9]Erik J. Bekkers
Template Matching via Densities on the Roto-Translation Group. IEEE Trans. Pattern Anal. Mach. Intell. 40(2): 452-466 (2018) - [j8]Jiong Zhang
Reconnection of Interrupted Curvilinear Structures via Cortically Inspired Completion for Ophthalmologic Images. IEEE Trans. Biomed. Eng. 65(5): 1151-1165 (2018) - [c10]Erik J. Bekkers, Maxime W. Lafarge, Mitko Veta, Koen A. J. Eppenhof
Roto-Translation Covariant Convolutional Networks for Medical Image Analysis. MICCAI (1) 2018: 440-448 - [i5]Erik J. Bekkers, Maxime W. Lafarge, Mitko Veta, Koen A. J. Eppenhof
Roto-Translation Covariant Convolutional Networks for Medical Image Analysis. CoRR abs/1804.03393 (2018) - 2017
- [j7]Alexey Mashtakov
Tracking of Lines in Spherical Images via Sub-Riemannian Geodesics in SO(3). J. Math. Imaging Vis. 58(2): 239-264 (2017) - [j6]Jiong Zhang
Retinal vessel delineation using a brain-inspired wavelet transform and random forest. Pattern Recognit. 69: 107-123 (2017) - [c9]Erik J. Bekkers
Vessel Tracking via Sub-Riemannian Geodesics on the Projective Line Bundle. GSI 2017: 773-781 - [c8]Michiel H. J. Janssen, Tom C. J. Dela Haije, Frank C. Martin, Erik J. Bekkers
The Hessian of Axially Symmetric Functions on SE(3) and Application in 3D Image Analysis. SSVM 2017: 643-655 - [i4]Michiel H. J. Janssen, A. J. E. M. Janssen, Erik J. Bekkers, Javier Oliván Bescós, Remco Duits:
Design and Processing of Invertible Orientation Scores of 3D Images for Enhancement of Complex Vasculature. CoRR abs/1707.02191 (2017) - 2016
- [j5]Bart M. ter Haar Romeny
Brain-inspired algorithms for retinal image analysis. Mach. Vis. Appl. 27(8): 1117-1135 (2016) - [j4]Jiong Zhang
Robust Retinal Vessel Segmentation via Locally Adaptive Derivative Frames in Orientation Scores. IEEE Trans. Medical Imaging 35(12): 2631-2644 (2016) - [c7]Samaneh Abbasi-Sureshjani, Iris Smit-Ockeloen, Erik J. Bekkers
Automatic detection of vascular bifurcations and crossings in retinal images using orientation scores. ISBI 2016: 189-192 - [i3]Erik J. Bekkers, Marco Loog, Bart M. ter Haar Romeny, Remco Duits:
Template Matching on the Roto-Translation Group. CoRR abs/1603.03304 (2016) - 2015
- [j3]Erik J. Bekkers
A PDE Approach to Data-Driven Sub-Riemannian Geodesics in SE(2). SIAM J. Imaging Sci. 8(4): 2740-2770 (2015) - [c6]Gonzalo Sanguinetti, Erik J. Bekkers
Sub-Riemannian Fast Marching in SE(2). CIARP 2015: 366-374 - [c5]Jiong Zhang
Robust and Fast Vessel Segmentation via Gaussian Derivatives in Orientation Scores. ICIAP (1) 2015: 537-547 - [c4]Erik J. Bekkers
Data-Driven Sub-Riemannian Geodesics in SE(2). SSVM 2015: 613-625 - 2014
- [j2]Erik J. Bekkers
A Multi-Orientation Analysis Approach to Retinal Vessel Tracking. J. Math. Imaging Vis. 49(3): 583-610 (2014) - [c3]Erik J. Bekkers
Training of Templates for Object Recognition in Invertible Orientation Scores: Application to Optic Nerve Head Detection in Retinal Images. EMMCVPR 2014: 464-477 - [c2]Erik J. Bekkers
Optic Nerve Head Detection via Group Correlations in Multi-orientation Transforms. ICIAR (2) 2014: 293-302 - [c1]Julius Hannink
Crossing-Preserving Multi-scale Vesselness. MICCAI (2) 2014: 603-610 - [i2]Julius Hannink, Remco Duits, Erik J. Bekkers:
Vesselness via Multiple Scale Orientation Scores. CoRR abs/1402.4963 (2014) - 2012
- [i1]Erik J. Bekkers, Remco Duits, Bart M. ter Haar Romeny, Tos Berendschot:
A New Retinal Vessel Tracking Method Based on Orientation Scores. CoRR abs/1212.3530 (2012)
2000 – 2009
- 2008
- [j1]Erik J. Bekkers, Charles A. Taylor:
Multiscale Vascular Surface Model Generation From Medical Imaging Data Using Hierarchical Features. IEEE Trans. Medical Imaging 27(3): 331-341 (2008)
Coauthor Index
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