14 citations · 18 across the 3 of their papers we have counts for
3 papers
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…
SIRE: scale-invariant, rotation-equivariant estimation of artery orientations using graph neural networks
Dieuwertje Alblas, Julian Suk, Christoph Brune +2
Blood vessel orientation as visualized in 3D medical images is an important descriptor of its geometry that can be used for centerline extraction and subsequent segmentation and vi…
Implicit Neural Representations for Generative Modeling of Living Cell Shapes
David Wiesner, Julian Suk, Sven Dummer +2
Methods allowing the synthesis of realistic cell shapes could help generate training data sets to improve cell tracking and segmentation in biomedical images. Deep generative model…