1 citations · 1 across the 5 of their papers we have counts for
5 papers
Longitudinal Flow Matching for Trajectory Modeling
Mohammad Mohaiminul Islam, Thijs P. Kuipers, Sharvaree Vadgama +4
Generative models for sequential data often struggle with sparsely sampled and high-dimensional trajectories, typically reducing the learning of dynamics to pairwise transitions. W…
CP: Leveraging Geometry for Conformal Prediction via Canonicalization
Putri A. van der Linden, Alexander Timans, Erik J. Bekkers
We study the problem of conformal prediction (CP) under geometric data shifts, where data samples are susceptible to transformations such as rotations or flips. While CP endows pre…
Learning Symmetries via Weight-Sharing with Doubly Stochastic Tensors
Putri A. van der Linden, Alejandro García-Castellanos, Sharvaree Vadgama +2
Group equivariance has emerged as a valuable inductive bias in deep learning, enhancing generalization, data efficiency, and robustness. Classically, group equivariant methods requ…
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…