32 citations · 119 across the 19 of their papers we have counts for
7 papers · 1 filter
When Does Equivariance Help? Canonical Alignment in Neural Fluid Surrogates
Patryk Rygiel, Julian Suk, Kak Khee Yeung +2
Neural surrogates can accelerate computational fluid dynamics (CFD) simulations by orders of magnitude, but practical deployment in engineering and healthcare applications requires…
Inpainting physics: self-supervised learning for context-driven fluid simulation
Jonas Weidner, Yeray Martin-Ruisanchez, Daniel Rueckert +2
Neural surrogate models for computational fluid dynamics (CFD) are typically trained as forward operators that map explicit problem specifications, such as geometry and boundary co…
ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain
Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna +70
This paper describes the 2nd edition of the ICML Topological Deep Learning Challenge that was hosted within the ICML 2024 ELLIS Workshop on Geometry-grounded Representation Learnin…
TopoBench: A Framework for Benchmarking Topological Deep Learning
Lev Telyatnikov, Guillermo Bernardez, Marco Montagna +34
This work introduces TopoBench, an open-source library designed to standardize benchmarking and accelerate research in topological deep learning (TDL). TopoBench decomposes TDL int…
SE(3) symmetry lets graph neural networks learn arterial velocity estimation from small datasets
Julian Suk, Christoph Brune, Jelmer M. Wolterink
Hemodynamic velocity fields in coronary arteries could be the basis of valuable biomarkers for diagnosis, prognosis and treatment planning in cardiovascular disease. Velocity field…
Mesh Neural Networks for SE(3)-Equivariant Hemodynamics Estimation on the Artery Wall
Julian Suk, Pim de Haan, Phillip Lippe +2
Computational fluid dynamics (CFD) is a valuable asset for patient-specific cardiovascular-disease diagnosis and prognosis, but its high computational demands hamper its adoption i…
Mesh convolutional neural networks for wall shear stress estimation in 3D artery models
Julian Suk, Pim de Haan, Phillip Lippe +2
Computational fluid dynamics (CFD) is a valuable tool for personalised, non-invasive evaluation of hemodynamics in arteries, but its complexity and time-consuming nature prohibit l…