Bekkers, Erik J

44 publications

ICLR 2026 AdS-GNN - A Conformally Equivariant Graph Neural Network Maksim Zhdanov, Nabil Iqbal, Erik J Bekkers, Patrick Forré

ICLR 2026 CORDS - Continuous Representations of Discrete Structures Tin Hadži Veljković, Erik J Bekkers, Michael Tiemann, Jan-Willem van de Meent

MIDL 2026 Geometry-Aware Cardiac MRI Representation Learning with Equivariant Neural Fields Jesse L. Wiers, David R. Wessels, Lukas P.A. Arts, Samuel Ruiperez-Campillo, Maarten Z.H. Kolk, Fleur V.Y. Tjong, Erik J. Bekkers

ICLR 2026 Riemannian Variational Flow Matching for Material and Protein Design Olga Zaghen, Floor Eijkelboom, Alison Pouplin, Cong Liu, Max Welling, Jan-Willem van de Meent, Erik J Bekkers

ICLRW 2025 AdS-GNN - A Conformally Equivariant Graph Neural Network Maksim Zhdanov, Nabil Iqbal, Erik J Bekkers, Patrick Forré

FTML 2025 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, 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

UAI 2025 CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Putri A Linden, Alexander Timans, Erik J Bekkers

ICLRW 2025 Clifford Group Equivariant Diffusion Models for 3D Molecular Generation Cong Liu, Sharvaree Vadgama, David Ruhe, Erik J Bekkers, Patrick Forré

ICML 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

NeurIPS 2025 Equivariant Eikonal Neural Networks: Grid-Free, Scalable Travel-Time Prediction on Homogeneous Spaces Alejandro García-Castellanos, David Wessels, Nicky J. van den Berg, Remco Duits, Daniel Pelt, Erik J Bekkers

ICLR 2025 Grounding Continuous Representations in Geometry: Equivariant Neural Fields David Wessels, David M Knigge, Riccardo Valperga, Samuele Papa, Sharvaree Vadgama, Efstratios Gavves, Erik J Bekkers

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

NeurIPS 2025 Probing Equivariance and Symmetry Breaking in Convolutional Networks Sharvaree Vadgama, Mohammad Mohaiminul Islam, Domas Buracas, Christian A Shewmake, Artem Moskalev, Erik J Bekkers

MIDL 2025 Self-Supervised Synthetic Cerebral Vessel Tree Generation Using Semantic Signed Distance Fields Thijs P. Kuipers, Praneeta R. Konduri, Erik J Bekkers, Henk Marquering

ICLRW 2025 Towards Variational Flow Matching on General Geometries Olga Zaghen, Floor Eijkelboom, Alison Pouplin, Erik J Bekkers

ICMLW 2024 E(n) Equivariant Message Passing Cellular Networks Veljko Kovac, Erik J Bekkers, Pietro Lio, Floor Eijkelboom

ICLRW 2024 Equivariant Neural Fields for Symmetry Preserving Continous PDE Forecasting David M Knigge, David Wessels, Riccardo Valperga, Samuele Papa, Stratis Gavves, Erik J Bekkers

ICLR 2024 Fast, Expressive $\mathrm{SE}(n)$ Equivariant Networks Through Weight-Sharing in Position-Orientation Space Erik J Bekkers, Sharvaree Vadgama, Rob Hesselink, Putri A Van der Linden, David W. Romero

MIDL 2024 Generating Cerebral Vessel Trees of Acute Ischemic Stroke Patients Using Conditional Set-Diffusion Thijs P. Kuipers, Praneeta R. Konduri, Henk Marquering, Erik J Bekkers

NeurIPS 2024 Learning Symmetries via Weight-Sharing with Doubly Stochastic Tensors Putri A. van der Linden, Alejandro García-Castellanos, Sharvaree Vadgama, Thijs P. Kuipers, Erik J. Bekkers

ICMLW 2024 Learning Symmetries via Weight-Sharing with Doubly Stochastic Tensors Putri A Van der Linden, Alejandro García Castellanos, Sharvaree Vadgama, Thijs P. Kuipers, Erik J Bekkers

NeurIPSW 2024 On Optimal Lifting to SE(2) in Equivariant Neural Networks Chase van de Geijn, Remco Duits, Erik J Bekkers

ICLRW 2024 Physics-Informed Geometric Regularization of Heterogeneous Reconstructions in Cryo-EM Victor Prins, Willem Diepeveen, Erik J Bekkers, Ozan Öktem

NeurIPS 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

ICMLW 2024 The Hidden Pitfalls of the Cosine Similarity Loss Andrew Draganov, Sharvaree Vadgama, Erik J Bekkers

ICMLW 2024 The NGT200 Dataset - Geometric Multi-View Isolated Sign Recognition Oline Ranum, David Wessels, Gomèr Otterspeer, Erik J Bekkers, Floris Roelofsen, Jari I. Andersen

MIDL 2024 Uncertainty-Aware Retinal Layer Segmentation in OCT Through Probabilistic Signed Distance Functions Mohammad Mohaiminul Islam, Coen Vente, Bart Liefers, Caroline Klaver, Erik J Bekkers, Clara I. Sánchez

TMLR 2024 Wavelet Networks: Scale-Translation Equivariant Learning from Raw Time-Series David W. Romero, Erik J Bekkers, Jakub M. Tomczak, Mark Hoogendoorn

ICLRW 2023 An Exploration of Conditioning Methods in Graph Neural Networks Yeskendir Koishekenov, Erik J Bekkers

ICMLW 2023 Can Strong Structural Encoding Reduce the Importance of Message Passing? Floor Eijkelboom, Erik J Bekkers, Michael M. Bronstein, Francesco Di Giovanni

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

ICCVW 2023 Geometric Contrastive Learning Yeskendir Koishekenov, Sharvaree P. Vadgama, Riccardo Valperga, Erik J. Bekkers

ICCVW 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

ICMLW 2023 Learned Gridification for Efficient Point Cloud Processing Putri A Van der Linden, David W. Romero, Erik J Bekkers

ICLR 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

ICMLW 2023 On Genuine Invariance Learning Without Weight-Tying Artem Moskalev, Anna Sepliarskaia, Erik J Bekkers, Arnold W.M. Smeulders

NeurIPSW 2023 Visual Scene Representation with Hierarchical Equivariant Sparse Coding Christian A Shewmake, Domas Buracas, Hansen Lillemark, Jinho Shin, Erik J Bekkers, Nina Miolane, Bruno Olshausen

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

ICML 2022 Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups David M. Knigge, David W Romero, Erik J Bekkers

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 Geometric and Physical Quantities Improve E(3) Equivariant Message Passing Johannes Brandstetter, Rob Hesselink, Elise van der Pol, Erik J Bekkers, Max Welling

NeurIPSW 2022 Kendall Shape-VAE : Learning Shapes in a Generative Framework Sharvaree Vadgama, Jakub Mikolaj Tomczak, Erik J Bekkers

NeurIPSW 2021 Towards Lightweight Controllable Audio Synthesis with Conditional Implicit Neural Representations Jan Zuiderveld, Marco Federici, Erik J Bekkers

ICLR 2020 B-Spline CNNs on Lie Groups Erik J Bekkers