44 citations · 157 across the 58 of their papers we have counts for
6 papers · 1 filter
Multimodal Graph-based Classification of Esophageal Motility Disorders
Alexander Geiger, Lars Wagner, Daniel Rueckert +3
Diagnosing esophageal motility disorders pose significant challenges due to the complexity of high-resolution impedance manometry (HRIM) data and variability in clinical interpreta…
What Cohort INRs Encode and Where to Freeze Them
Vasiliki Sideri-Lampretsa, Sophie Starck, Robbie Holland +2
Reusing the early layers of cohort-trained INRs as initialization for new signals has been shown to accelerate and improve signal fitting, yet it remains unclear which layers of th…
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…
On the notion of missingness for path attribution explainability methods in medical settings: Guiding the selection of medically meaningful baselines
Alexander Geiger, Lars Wagner, Daniel Rueckert +2
The explainability of deep learning models remains a significant challenge, particularly in the medical domain where interpretable outputs are essential for clinical trust and tran…
Neural Network Surrogate and Projected Gradient Descent for Fast and Reliable Finite Element Model Calibration: a Case Study on an Intervertebral Disc
Matan Atad, Gabriel Gruber, Marx Ribeiro +7
Accurate calibration of finite element (FE) models is essential across various biomechanical applications, including human intervertebral discs (IVDs), to ensure their reliability…
On Discprecncies between Perturbation Evaluations of Graph Neural Network Attributions
Razieh Rezaei, Alireza Dizaji, Ashkan Khakzar +3
Neural networks are increasingly finding their way into the realm of graphs and modeling relationships between features. Concurrently graph neural network explanation approaches ar…