2 citations · 5 across the 14 of their papers we have counts for
6 papers · 1 filter
Uncertainty-aware retinal layer segmentation in OCT through probabilistic signed distance functions
Mohammad Mohaiminul Islam, Coen de Vente, Bart Liefers +3
In this paper, we present a new approach for uncertainty-aware retinal layer segmentation in Optical Coherence Tomography (OCT) scans using probabilistic signed distance functions…
The NGT200 Dataset: Geometric Multi-View Isolated Sign Recognition
Oline Ranum, David R. Wessels, Gomer Otterspeer +3
Sign Language Processing (SLP) provides a foundation for a more inclusive future in language technology; however, the field faces several significant challenges that must be addres…
HyperSteiner: Computing Heuristic Hyperbolic Steiner Minimal Trees
Alejandro García-Castellanos, Aniss Aiman Medbouhi, Giovanni Luca Marchetti +2
We propose HyperSteiner -- an efficient heuristic algorithm for computing Steiner minimal trees in the hyperbolic space. HyperSteiner extends the Euclidean Smith-Lee-Liebman algori…
The Hidden Pitfalls of the Cosine Similarity Loss
Andrew Draganov, Sharvaree Vadgama, Erik J. Bekkers
We show that the gradient of the cosine similarity between two points goes to zero in two under-explored settings: (1) if a point has large magnitude or (2) if the points are on op…
Space-Time Continuous PDE Forecasting using Equivariant Neural Fields
David M. Knigge, David R. Wessels, Riccardo Valperga +4
Recently, Conditional Neural Fields (NeFs) have emerged as a powerful modelling paradigm for PDEs, by learning solutions as flows in the latent space of the Conditional NeF. Althou…
Grounding Continuous Representations in Geometry: Equivariant Neural Fields
David R Wessels, David M Knigge, Samuele Papa +4
Conditional Neural Fields (CNFs) are increasingly being leveraged as continuous signal representations, by associating each data-sample with a latent variable that conditions a sha…