4 papers
Sharp Convergence Rates of Empirical Unbalanced Optimal Transport for Spatio-Temporal Point Processes
Marina Struleva, Shayan Hundrieser, Dominic Schuhmacher +1
We statistically analyze empirical plug-in estimators for unbalanced optimal transport (UOT) formalisms, focusing on the Kantorovich-Rubinstein distance, between general intensity…
Block Graph Neural Networks for tumor heterogeneity prediction
Marianne Abémgnigni Njifon, Tobias Weber, Viktor Bezborodov +2
Accurate tumor classification is essential for selecting effective treatments, but current methods have limitations. Standard tumor grading, which categorizes tumors based on cell…
Stein's Method for Spatial Random Graphs
Dominic Schuhmacher, Leoni Carla Wirth
In this article, we derive Stein's method for approximating a spatial random graph by a generalised random geometric graph, which has vertices given by a finite Gibbs point process…
Discrete versus continuous domain models for disease mapping
Garyfallos Konstantinoudis, Dominic Schuhmacher, Håvard Rue +1
The main goal of disease mapping is to estimate disease risk and identify high-risk areas. Such analyses are hampered by the limited geographical resolution of the available data.…