Practicable Simulation-Free Model Order Reduction by Nonlinear Moment Matching. - Maria Cruz Varona; Raphael Gebhart; Julian Suk; Boris Lohmann (CoRR, 2019)

Mesh Convolutional Neural Networks for Wall Shear Stress Estimation in 3D Artery Models. - Julian Suk; Pim de Haan; Phillip Lippe; Christoph Brune; Jelmer M. Wolterink (STACOM@MICCAI, 2021)

Implicit Neural Representations for Generative Modeling of Living Cell Shapes. - David Wiesner; Julian Suk; Sven Dummer; David Svoboda; Jelmer M. Wolterink (MICCAI (4), 2022)

SE(3) Symmetry Lets Graph Neural Networks Learn Arterial Velocity Estimation from Small Datasets. - Julian Suk; Christoph Brune; Jelmer M. Wolterink (FIMH, 2023)

LaB-GATr: Geometric Algebra Transformers for Large Biomedical Surface and Volume Meshes. - Julian Suk; Baris Imre; Jelmer M. Wolterink (MICCAI (12), 2024)

Mesh neural networks for SE(3)-equivariant hemodynamics estimation on the artery wall. - Julian Suk; Pim de Haan; Phillip Lippe; Christoph Brune; Jelmer M. Wolterink (Comput. Biol. Medicine, 2024)

Physics-informed graph neural networks for flow field estimation in carotid arteries. - Julian Suk; Dieuwertje Alblas; Barbara A. Hutten; Albert Wiegman; Christoph Brune; Pim van Ooij; Jelmer M. Wolterink (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)

Generative modeling of living cells with SO(3)-equivariant implicit neural representations. - David Wiesner; Julian Suk; Sven Dummer; Tereza Necasová; Vladimír Ulman; David Svoboda; Jelmer M. Wolterink (Medical Image Anal., 2024)

Learning hemodynamic scalar fields on coronary artery meshes: A benchmark of geometric deep learning models. - Guido Nannini; Julian Suk; Patryk Rygiel; Simone Saitta; Luca Mariani; Riccardo Maranga; Andrea Baggiano; Gianluca Pontone; Jelmer M. Wolterink; Alberto Redaelli (Comput. Biol. Medicine, 2025)

Deep vectorised operators for pulsatile hemodynamics estimation in coronary arteries from a steady-state prior. - Julian Suk; Guido Nannini; Patryk Rygiel; Christoph Brune; Gianluca Pontone; Alberto Redaelli; Jelmer M. Wolterink (Comput. Methods Programs Biomed., 2025)

SIRE: Scale-invariant, rotation-equivariant estimation of artery orientations using graph neural networks. - Dieuwertje Alblas; Julian Suk; Christoph Brune; Kak Khee Yeung; Jelmer M. Wolterink (Medical Image Anal., 2025)

Learning Hemodynamic Scalar Fields on Coronary Artery Meshes: A Benchmark of Geometric Deep Learning Models. - Guido Nannini; Julian Suk; Patryk Rygiel; Simone Saitta; Luca Mariani; Riccardo Maragna; Andrea Baggiano; Gianluca Pontone; Jelmer M. Wolterink; Alberto Redaelli (CoRR, 2025)

Active Learning for Deep Learning-Based Hemodynamic Parameter Estimation. - Patryk Rygiel; Julian Suk; Kak Khee Yeung; Christoph Brune; Jelmer M. Wolterink (CoRR, 2025)

Geometric deep learning for local growth prediction on abdominal aortic aneurysm surfaces. - Dieuwertje Alblas; Patryk Rygiel; Julian Suk; Kaj O. Kappe; Marieke Hofman; Christoph Brune; Kak Khee Yeung; Jelmer M. Wolterink (CoRR, 2025)

Wall Shear Stress Estimation in Abdominal Aortic Aneurysms: Towards Generalisable Neural Surrogate Models. - Patryk Rygiel; Julian Suk; Christoph Brune; Kak Khee Yeung; Jelmer M. Wolterink (CoRR, 2025)