Erik J. Bekkers

123 papers A* 15A 2C 1Journal 74Unranked 29

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	CORDS: Continuous Representations of Discrete Structures. CoRR Tin Hadzi Veljkovic, Erik J. Bekkers, Michael Tiemann, Jan-Willem van de Meent
2026	J	`jnl`	Dual-Phase Cross-Modal Contrastive Learning for CMR-Guided ECG Representations for Cardiovascular Disease Assessment. CoRR Laura Alvarez-Florez, Angel Bujalance-Gomez, Femke Raijmakers, Samuel Ruipérez-Campillo, Maarten Z. Kolk, Jesse Wiers, Julia E. Vogt, Erik J. Bekkers, Ivana Isgum, Fleur V. Y. Tjong
2026	J	`jnl`	Generalized Reduction to the Isotropy for Flexible Equivariant Neural Fields. CoRR Alejandro García-Castellanos, Gijs Bellaard, Remco Duits, Daniël M. Pelt, Erik J. Bekkers
2026	J	`jnl`	Synthesis of Late Gadolinium Enhancement Images via Implicit Neural Representations for Cardiac Scar Segmentation. CoRR Soufiane Ben Haddou, Laura Alvarez-Florez, Erik J. Bekkers, Fleur V. Y. Tjong, Ahmad S. Amin, Connie R. Bezzina, Ivana Isgum
2026	J	`jnl`	Unplugging a Seemingly Sentient Machine Is the Rational Choice - A Metaphysical Perspective. CoRR Erik J. Bekkers, Anna Ciaunica
2025	J	`jnl`	AdS-GNN - a Conformally Equivariant Graph Neural Network. CoRR Maksim Zhdanov, Nabil Iqbal, Erik J. Bekkers, Patrick Forré
2025	J	`jnl`	Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. Found. Trends Mach. Learn. 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, Alex Strasser, Haiyang Yu, Yuqing Xie, Xiang Fu, 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
2025	A	`conf`	CP UAI Putri A. van der Linden, Alexander Timans, Erik J. Bekkers
2025	J	`jnl`	CP CoRR Putri A. van der Linden, Alexander Timans, Erik J. Bekkers
2025	J	`jnl`	Clifford Group Equivariant Diffusion Models for 3D Molecular Generation. CoRR Cong Liu, Sharvaree Vadgama, David Ruhe, Erik J. Bekkers, Patrick Forré
2025	A*	`conf`	Controlled Generation with Equivariant Variational Flow Matching. ICML Floor Eijkelboom, Heiko Zimmermann, Sharvaree Vadgama, Erik J. Bekkers, Max Welling, Christian A. Naesseth, Jan-Willem van de Meent
2025	J	`jnl`	Controlled Generation with Equivariant Variational Flow Matching. CoRR Floor Eijkelboom, Heiko Zimmermann, Sharvaree Vadgama, Erik J. Bekkers, Max Welling, Christian A. Naesseth, Jan-Willem van de Meent
2025	J	`jnl`	Equivariant Eikonal Neural Networks: Grid-Free, Scalable Travel-Time Prediction on Homogeneous Spaces. CoRR Alejandro García-Castellanos, David R. Wessels, Nicky J. van den Berg, Remco Duits, Daniël M. Pelt, Erik J. Bekkers
2025	A*	`conf`	Grounding Continuous Representations in Geometry: Equivariant Neural Fields. ICLR David R. Wessels, David M. Knigge, Riccardo Valperga, Samuele Papa, Sharvaree P. Vadgama, Efstratios Gavves, Erik J. Bekkers
2025	J	`jnl`	Homomorphism distortion: A metric to distinguish them all and in the latent space bind them. CoRR Martin Carrasco, Olga Zaghen, Erik J. Bekkers, Bastian Rieck
2025	A	`conf`	HyperSteiner: Computing Heuristic Hyperbolic Steiner Minimal Trees. ALENEX Alejandro García-Castellanos, Aniss Aiman Medbouhi, Giovanni Luca Marchetti, Erik J. Bekkers, Danica Kragic
2025	J	`jnl`	Longitudinal Flow Matching for Trajectory Modeling. CoRR Mohammad Mohaiminul Islam, Thijs P. Kuipers, Sharvaree P. Vadgama, Coen de Vente, Afsana Khan, Clara I. Sánchez, Erik J. Bekkers
2025	J	`jnl`	On Equivariant Model Selection through the Lens of Uncertainty. CoRR Putri A. van der Linden, Alexander Timans, Dharmesh Tailor, Erik J. Bekkers
2025	A*	`conf`	On the Importance of Embedding Norms in Self-Supervised Learning. ICML Andrew Draganov, Sharvaree Vadgama, Sebastian Damrich, Jan Niklas Böhm, Lucas Maes, Dmitry Kobak, Erik J. Bekkers
2025	J	`jnl`	On the Importance of Embedding Norms in Self-Supervised Learning. CoRR Andrew Draganov, Sharvaree P. Vadgama, Sebastian Damrich, Jan Niklas Böhm, Lucas Maes, Dmitry Kobak, Erik J. Bekkers
2025	J	`jnl`	On the Utility of Equivariance and Symmetry Breaking in Deep Learning Architectures on Point Clouds. CoRR Sharvaree P. Vadgama, Mohammad Mohaiminul Islam, Domas Buracus, Christian Shewmake, Erik J. Bekkers
2025	—	`conf`	Orientation Scores Should Be a Piece of Cake. GSI (3) Finn M. Sherry, Chase van de Geijn, Erik J. Bekkers, Remco Duits
2025	J	`jnl`	Orientation Scores should be a Piece of Cake. CoRR Finn M. Sherry, Chase van de Geijn, Erik J. Bekkers, Remco Duits
2025	J	`jnl`	Platonic Transformers: A Solid Choice For Equivariance. CoRR Mohammad Mohaiminul Islam, Rishabh Anand, David R. Wessels, Friso de Kruiff, Thijs P. Kuipers, Rex Ying, Clara I. Sánchez, Sharvaree Vadgama, Georg Bökman, Erik J. Bekkers
2025	J	`jnl`	Randomized HyperSteiner: A Stochastic Delaunay Triangulation Heuristic for the Hyperbolic Steiner Minimal Tree. CoRR Aniss Aiman Medbouhi, Alejandro García-Castellanos, Giovanni Luca Marchetti, Daniël M. Pelt, Erik J. Bekkers, Danica Kragic
2025	J	`jnl`	SE(3) group convolutional neural networks and a study on group convolutions and equivariance for DWI segmentation. Frontiers Artif. Intell. Renfei Liu, François Lauze, Erik J. Bekkers, Sune Darkner, Kenny Erleben
2025	J	`jnl`	Towards Variational Flow Matching on General Geometries. CoRR Olga Zaghen, Floor Eijkelboom, Alison Pouplin, Erik J. Bekkers
2024	—	`conf`	E(n) Equivariant Message Passing Cellular Networks. GRaM Veljko Kovac, Erik J. Bekkers, Pietro Lió, Floor Eijkelboom
2024	J	`jnl`	E(n) Equivariant Message Passing Cellular Networks. CoRR Veljko Kovac, Erik J. Bekkers, Pietro Liò, Floor Eijkelboom
2024	A*	`conf`	Fast, Expressive SE(n) Equivariant Networks through Weight-Sharing in Position-Orientation Space. ICLR Erik J. Bekkers, Sharvaree P. Vadgama, Rob Hesselink, Putri A. van der Linden, David W. Romero
2024	—	`conf`	Generating Cerebral Vessel Trees of Acute Ischemic Stroke Patients using Conditional Set-Diffusion. MIDL Thijs P. Kuipers, Praneeta Konduri, Henk A. Marquering, Erik J. Bekkers
2024	J	`jnl`	Grounding Continuous Representations in Geometry: Equivariant Neural Fields. CoRR David R. Wessels, David M. Knigge, Samuele Papa, Riccardo Valperga, Sharvaree P. Vadgama, Efstratios Gavves, Erik J. Bekkers
2024	J	`jnl`	HyperSteiner: Computing Heuristic Hyperbolic Steiner Minimal Trees. CoRR Alejandro García-Castellanos, Aniss Aiman Medbouhi, Giovanni Luca Marchetti, Erik J. Bekkers, Danica Kragic
2024	—	`conf`	ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain. GRaM 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 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
2024	J	`jnl`	ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain. CoRR 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
2024	J	`jnl`	Learning Symmetries via Weight-Sharing with Doubly Stochastic Tensors. CoRR Putri A. van der Linden, Alejandro García-Castellanos, Sharvaree P. Vadgama, Thijs P. Kuipers, Erik J. Bekkers
2024	A*	`conf`	Learning symmetries via weight-sharing with doubly stochastic tensors. NeurIPS Putri A. van der Linden, Alejandro García-Castellanos, Sharvaree P. Vadgama, Thijs P. Kuipers, Erik J. Bekkers
2024	—	`conf`	Preface to Geometry-grounded Representation Learning and Generative Modeling (GRaM) Workshop. GRaM Sharvaree Vadgama, Erik J. Bekkers, Alison Pouplin, Sékou-Oumar Kaba, Robin Walters, Hannah Lawrence, Tegan Emerson, Henry Kvinge, Jakub M. Tomczak, Stefanie Jegelka
2024	—	`ed.`	Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM) at ICML 2024, 29 July 2024, Vienna, Austria GRaM Sharvaree Vadgama, Erik J. Bekkers, Alison Pouplin, Sékou-Oumar Kaba, Robin Walters, Hannah Lawrence, Tegan Emerson, Henry Kvinge, Jakub M. Tomczak, Stefanie Jegelka
2024	J	`jnl`	Pullback Flow Matching on Data Manifolds. CoRR Friso de Kruiff, Erik J. Bekkers, Ozan Öktem, Carola-Bibiane Schönlieb, Willem Diepeveen
2024	A*	`conf`	Space-Time Continuous PDE Forecasting using Equivariant Neural Fields. NeurIPS David M. Knigge, David R. Wessels, Riccardo Valperga, Samuele Papa, Jan-Jakob Sonke, Erik J. Bekkers, Efstratios Gavves
2024	J	`jnl`	Space-Time Continuous PDE Forecasting using Equivariant Neural Fields. CoRR David M. Knigge, David R. Wessels, Riccardo Valperga, Samuele Papa, Jan-Jakob Sonke, Efstratios Gavves, Erik J. Bekkers
2024	J	`jnl`	The Hidden Pitfalls of the Cosine Similarity Loss. CoRR Andrew Draganov, Sharvaree P. Vadgama, Erik J. Bekkers
2024	—	`conf`	The NGT200 Dataset: Geometric Multi-View Isolated Sign Recognition. GRaM Oline Ranum, David R. Wessels, Gomer Otterspeer, Erik J. Bekkers, Floris Roelofsen, Jari I. Andersen
2024	J	`jnl`	The NGT200 Dataset: Geometric Multi-View Isolated Sign Recognition. CoRR Oline Ranum, David R. Wessels, Gomer Otterspeer, Erik J. Bekkers, Floris Roelofsen, Jari I. Andersen
2024	—	`conf`	Uncertainty-aware retinal layer segmentation in OCT through probabilistic signed distance functions. MIDL Mohammad Mohaiminul Islam, Coen de Vente, Bart Liefers, Caroline Klaver, Erik J. Bekkers, Clara I. Sánchez
2024	J	`jnl`	Uncertainty-aware retinal layer segmentation in OCT through probabilistic signed distance functions. CoRR Mohammad Mohaiminul Islam, Coen de Vente, Bart Liefers, Caroline Klaver, Erik J. Bekkers, Clara I. Sánchez
2024	J	`jnl`	Wavelet Networks: Scale-Translation Equivariant Learning From Raw Time-Series. Trans. Mach. Learn. Res. David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
2023	J	`jnl`	An Exploration of Conditioning Methods in Graph Neural Networks. CoRR Yeskendir Koishekenov, Erik J. Bekkers
2023	J	`jnl`	Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. CoRR 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
2023	—	`conf`	Can strong structural encoding reduce the importance of Message Passing? TAG-ML Floor Eijkelboom, Erik J. Bekkers, Michael M. Bronstein, Francesco Di Giovanni
2023	J	`jnl`	Can strong structural encoding reduce the importance of Message Passing? CoRR Floor Eijkelboom, Erik J. Bekkers, Michael M. Bronstein, Francesco Di Giovanni
2023	—	`conf`	Continuous Kendall Shape Variational Autoencoders. GSI (1) Sharvaree P. Vadgama, Jakub M. Tomczak, Erik J. Bekkers
2023	A*	`conf`	E(n) Equivariant Message Passing Simplicial Networks. ICML Floor Eijkelboom, Rob Hesselink, Erik J. Bekkers
2023	J	`jnl`	E(n) Equivariant Message Passing Simplicial Networks. CoRR Floor Eijkelboom, Rob Hesselink, Erik J. Bekkers
2023	J	`jnl`	Fast, Expressive SE(n) Equivariant Networks through Weight-Sharing in Position-Orientation Space. CoRR Erik J. Bekkers, Sharvaree P. Vadgama, Rob D. Hesselink, Putri A. van der Linden, David W. Romero
2023	—	`conf`	Geometric Contrastive Learning. ICCV (Workshops) Yeskendir Koishekenov, Sharvaree P. Vadgama, Riccardo Valperga, Erik J. Bekkers
2023	—	`conf`	Geometric Superpixel Representations for Efficient Image Classification with Graph Neural Networks. ICCV (Workshops) Radu A. Cosma, Lukas Knobel, Putri A. van der Linden, David M. Knigge, Erik J. Bekkers
2023	J	`jnl`	Latent Field Discovery In Interacting Dynamical Systems With Neural Fields. CoRR Miltiadis Kofinas, Erik J. Bekkers, Naveen Shankar Nagaraja, Efstratios Gavves
2023	A*	`conf`	Latent Field Discovery in Interacting Dynamical Systems with Neural Fields. NeurIPS Miltiadis Kofinas, Erik J. Bekkers, Naveen Shankar Nagaraja, Efstratios Gavves
2023	—	`conf`	Learned Gridification for Efficient Point Cloud Processing. TAG-ML Putri A. van der Linden, David W. Romero, Erik J. Bekkers
2023	J	`jnl`	Learned Gridification for Efficient Point Cloud Processing. CoRR Putri A. van der Linden, David W. Romero, Erik J. Bekkers
2023	—	`conf`	Modeling Barrett's Esophagus Progression Using Geometric Variational Autoencoders. CaPTion@MICCAI Vivien van Veldhuizen, Sharvaree P. Vadgama, Onno J. de Boer, Sybren L. Meijer, Erik J. Bekkers
2023	A*	`conf`	Modelling Long Range Dependencies in $N$D: From Task-Specific to a General Purpose CNN. ICLR David M. Knigge, David W. Romero, Albert Gu, Efstratios Gavves, Erik J. Bekkers, Jakub Mikolaj Tomczak, Mark Hoogendoorn, Jan-Jakob Sonke
2023	J	`jnl`	Modelling Long Range Dependencies in N-D: From Task-Specific to a General Purpose CNN. CoRR David M. Knigge, David W. Romero, Albert Gu, Efstratios Gavves, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn, Jan-Jakob Sonke
2023	—	`conf`	On genuine invariance learning without weight-tying. TAG-ML Artem Moskalev, Anna Sepliarskaia, Erik J. Bekkers, Arnold W. M. Smeulders
2023	J	`jnl`	On genuine invariance learning without weight-tying. CoRR Artem Moskalev, Anna Sepliarskaia, Erik J. Bekkers, Arnold W. M. Smeulders
2023	J	`jnl`	PDE-Based Group Equivariant Convolutional Neural Networks. J. Math. Imaging Vis. Bart M. N. Smets, Jim Portegies, Erik J. Bekkers, Remco Duits
2023	—	`conf`	Regular SE(3) Group Convolutions for Volumetric Medical Image Analysis. MICCAI (3) Thijs P. Kuipers, Erik J. Bekkers
2023	J	`jnl`	Regular SE(3) Group Convolutions for Volumetric Medical Image Analysis. CoRR Thijs P. Kuipers, Erik J. Bekkers
2022	A*	`conf`	CKConv: Continuous Kernel Convolution For Sequential Data. ICLR David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub Mikolaj Tomczak, Mark Hoogendoorn
2022	—	`conf`	Deep Learning for Ventricular Arrhythmia Prediction Using Fibrosis Segmentations on Cardiac MRI Data. CinC 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
2022	A*	`conf`	Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups. ICML David M. Knigge, David W. Romero, Erik J. Bekkers
2022	A*	`conf`	FlexConv: Continuous Kernel Convolutions With Differentiable Kernel Sizes. ICLR David W. Romero, Robert-Jan Bruintjes, Jakub Mikolaj Tomczak, Erik J. Bekkers, Mark Hoogendoorn, Jan van Gemert
2022	—	`ed.`	Geometric Deep Learning in Medical Image Analysis, 18 November 2022, Amsterdam, The Netherlands GeoMedIA Erik J. Bekkers, Jelmer M. Wolterink, Angelica I. Avilés-Rivero
2022	A*	`conf`	Geometric and Physical Quantities improve E(3) Equivariant Message Passing. ICLR Johannes Brandstetter, Rob Hesselink, Elise van der Pol, Erik J. Bekkers, Max Welling
2022	—	`conf`	Group Convolutional Neural Networks for DWI Segmentation. GeoMedIA Renfei Liu, François Lauze, Erik J. Bekkers, Kenny Erleben, Sune Darkner
2022	—	`conf`	Preface. GeoMedIA Erik J. Bekkers, Jelmer M. Wolterink, Angelica I. Avilés-Rivero
2022	J	`jnl`	Towards a General Purpose CNN for Long Range Dependencies in ND. CoRR David W. Romero, David M. Knigge, Albert Gu, Erik J. Bekkers, Efstratios Gavves, Jakub M. Tomczak, Mark Hoogendoorn
2022	—	`conf`	Weakly-Supervised Deep Learning for Left Ventricle Fibrosis Segmentation in Cardiac MRI Using Image-Level Labels. CinC 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
2021	J	`jnl`	CKConv: Continuous Kernel Convolution For Sequential Data. CoRR David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
2021	J	`jnl`	ChebLieNet: Invariant Spectral Graph NNs Turned Equivariant by Riemannian Geometry on Lie Groups. CoRR Hugo Aguettaz, Erik J. Bekkers, Michaël Defferrard
2021	—	`conf`	Equivariant Deep Learning via Morphological and Linear Scale Space PDEs on the Space of Positions and Orientations. SSVM Remco Duits, Bart M. N. Smets, Erik J. Bekkers, Jim Portegies
2021	J	`jnl`	Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups. CoRR David M. Knigge, David W. Romero, Erik J. Bekkers
2021	J	`jnl`	FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes. CoRR David W. Romero, Robert-Jan Bruintjes, Jakub M. Tomczak, Erik J. Bekkers, Mark Hoogendoorn, Jan C. van Gemert
2021	J	`jnl`	Geometric and Physical Quantities improve E(3) Equivariant Message Passing. CoRR Johannes Brandstetter, Rob Hesselink, Elise van der Pol, Erik J. Bekkers, Max Welling
2021	J	`jnl`	Interpretable ECG classification via a query-based latent space traversal (qLST). CoRR 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
2021	J	`jnl`	Roto-translation equivariant convolutional networks: Application to histopathology image analysis. Medical Image Anal. Maxime W. Lafarge, Erik J. Bekkers, Josien P. W. Pluim, Remco Duits, Mitko Veta
2021	J	`jnl`	Towards Lightweight Controllable Audio Synthesis with Conditional Implicit Neural Representations. CoRR Jan Zuiderveld, Marco Federici, Erik J. Bekkers
2020	A*	`conf`	Attentive Group Equivariant Convolutional Networks. ICML David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
2020	J	`jnl`	Attentive Group Equivariant Convolutional Networks. CoRR David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
2020	A*	`conf`	B-Spline CNNs on Lie groups. ICLR Erik J. Bekkers
2020	J	`jnl`	PDE-based Group Equivariant Convolutional Neural Networks. CoRR Bart M. N. Smets, Jim Portegies, Erik J. Bekkers, Remco Duits
2020	J	`jnl`	Roto-Translation Equivariant Convolutional Networks: Application to Histopathology Image Analysis. CoRR Maxime W. Lafarge, Erik J. Bekkers, Josien P. W. Pluim, Remco Duits, Mitko Veta
2020	J	`jnl`	Wavelet Networks: Scale Equivariant Learning From Raw Waveforms. CoRR David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
2019	J	`jnl`	B-Spline CNNs on Lie Groups. CoRR Erik J. Bekkers
2019	J	`jnl`	Fourier Transform on the Homogeneous Space of 3D Positions and Orientations for Exact Solutions to Linear PDEs. Entropy Remco Duits, Erik J. Bekkers, Alexey Mashtakov
2018	J	`jnl`	Design and Processing of Invertible Orientation Scores of 3D Images. J. Math. Imaging Vis. Michiel Janssen, A. J. E. M. Janssen, Erik J. Bekkers, Javier Oliván Bescós, Remco Duits
2018	J	`jnl`	Nilpotent Approximations of Sub-Riemannian Distances for Fast Perceptual Grouping of Blood Vessels in 2D and 3D. J. Math. Imaging Vis. Erik J. Bekkers, Da Chen, Jorg M. Portegies
2018	J	`jnl`	Reconnection of Interrupted Curvilinear Structures via Cortically Inspired Completion for Ophthalmologic Images. IEEE Trans. Biomed. Eng. 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
2018	—	`conf`	Roto-Translation Covariant Convolutional Networks for Medical Image Analysis. MICCAI (1) Erik J. Bekkers, Maxime W. Lafarge, Mitko Veta, Koen A. J. Eppenhof, Josien P. W. Pluim, Remco Duits
2018	J	`jnl`	Roto-Translation Covariant Convolutional Networks for Medical Image Analysis. CoRR Erik J. Bekkers, Maxime W. Lafarge, Mitko Veta, Koen A. J. Eppenhof, Josien P. W. Pluim, Remco Duits
2018	J	`jnl`	Template Matching via Densities on the Roto-Translation Group. IEEE Trans. Pattern Anal. Mach. Intell. Erik J. Bekkers, Marco Loog, Bart M. ter Haar Romeny, Remco Duits
2017	J	`jnl`	Design and Processing of Invertible Orientation Scores of 3D Images for Enhancement of Complex Vasculature. CoRR Michiel H. J. Janssen, A. J. E. M. Janssen, Erik J. Bekkers, Javier Oliván Bescós, Remco Duits
2017	J	`jnl`	Retinal vessel delineation using a brain-inspired wavelet transform and random forest. Pattern Recognit. Jiong Zhang, Yuan Chen, Erik J. Bekkers, Meili Wang, Behdad Dashtbozorg, Bart M. ter Haar Romeny
2017	—	`conf`	The Hessian of Axially Symmetric Functions on SE(3) and Application in 3D Image Analysis. SSVM Michiel H. J. Janssen, Tom C. J. Dela Haije, Frank C. Martin, Erik J. Bekkers, Remco Duits
2017	J	`jnl`	Tracking of Lines in Spherical Images via Sub-Riemannian Geodesics in SO(3). J. Math. Imaging Vis. Alexey Mashtakov, Remco Duits, Yuri Sachkov, Erik J. Bekkers, Ivan Beschastnyi
2017	—	`conf`	Vessel Tracking via Sub-Riemannian Geodesics on the Projective Line Bundle. GSI Erik J. Bekkers, Remco Duits, Alexey Mashtakov, Yuri Sachkov
2016	—	`conf`	Automatic detection of vascular bifurcations and crossings in retinal images using orientation scores. ISBI Samaneh Abbasi-Sureshjani, Iris Smit-Ockeloen, Erik J. Bekkers, Behdad Dashtbozorg, Bart M. ter Haar Romeny
2016	J	`jnl`	Brain-inspired algorithms for retinal image analysis. Mach. Vis. Appl. 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
2016	J	`jnl`	Robust Retinal Vessel Segmentation via Locally Adaptive Derivative Frames in Orientation Scores. IEEE Trans. Medical Imaging Jiong Zhang, Behdad Dashtbozorg, Erik J. Bekkers, Josien P. W. Pluim, Remco Duits, Bart M. ter Haar Romeny
2016	J	`jnl`	Template Matching on the Roto-Translation Group. CoRR Erik J. Bekkers, Marco Loog, Bart M. ter Haar Romeny, Remco Duits
2015	J	`jnl`	A PDE Approach to Data-Driven Sub-Riemannian Geodesics in SE(2). SIAM J. Imaging Sci. Erik J. Bekkers, Remco Duits, Alexey Mashtakov, Gonzalo R. Sanguinetti
2015	—	`conf`	Data-Driven Sub-Riemannian Geodesics in SE(2). SSVM Erik J. Bekkers, Remco Duits, Alexey Mashtakov, Gonzalo R. Sanguinetti
2015	—	`conf`	Robust and Fast Vessel Segmentation via Gaussian Derivatives in Orientation Scores. ICIAP (1) Jiong Zhang, Erik J. Bekkers, Samaneh Abbasi-Sureshjani, Behdad Dashtbozorg, Bart M. ter Haar Romeny
2015	C	`conf`	Sub-Riemannian Fast Marching in SE(2). CIARP Gonzalo Sanguinetti, Erik J. Bekkers, Remco Duits, Michiel H. J. Janssen, Alexey Mashtakov, Jean-Marie Mirebeau
2014	J	`jnl`	A Multi-Orientation Analysis Approach to Retinal Vessel Tracking. J. Math. Imaging Vis. Erik J. Bekkers, Remco Duits, Tos Berendschot, Bart M. ter Haar Romeny
2014	—	`conf`	Crossing-Preserving Multi-scale Vesselness. MICCAI (2) Julius Hannink, Remco Duits, Erik J. Bekkers
2014	—	`conf`	Optic Nerve Head Detection via Group Correlations in Multi-orientation Transforms. ICIAR (2) Erik J. Bekkers, Remco Duits, Bart M. ter Haar Romeny
2014	—	`conf`	Training of Templates for Object Recognition in Invertible Orientation Scores: Application to Optic Nerve Head Detection in Retinal Images. EMMCVPR Erik J. Bekkers, Remco Duits, Marco Loog
2014	J	`jnl`	Vesselness via Multiple Scale Orientation Scores. CoRR Julius Hannink, Remco Duits, Erik J. Bekkers
2012	J	`jnl`	A New Retinal Vessel Tracking Method Based on Orientation Scores CoRR Erik J. Bekkers, Remco Duits, Bart M. ter Haar Romeny, Tos Berendschot
2008	J	`jnl`	Multiscale Vascular Surface Model Generation From Medical Imaging Data Using Hierarchical Features. IEEE Trans. Medical Imaging Erik J. Bekkers, Charles A. Taylor