3 citations · 5 across the 4 of their papers we have counts for
5 papers
Towards Robust Foundation Models for Digital Pathology
Jonah Kömen, Edwin D. de Jong, Julius Hense +9
Biomedical Foundation Models (FMs) are rapidly transforming AI-enabled healthcare research and entering clinical validation. However, their susceptibility to learning non-biologica…
Do Histopathological Foundation Models Eliminate Batch Effects? A Comparative Study
Jonah Kömen, Hannah Marienwald, Jonas Dippel +1
Deep learning has led to remarkable advancements in computational histopathology, e.g., in diagnostics, biomarker prediction, and outcome prognosis. Yet, the lack of annotated data…
Estimation of multiple mean vectors in high dimension
Gilles Blanchard, Jean-Baptiste Fermanian, Hannah Marienwald
We endeavour to estimate numerous multi-dimensional means of various probability distributions on a common space based on independent samples. Our approach involves forming estimat…
High-Dimensional Multi-Task Averaging and Application to Kernel Mean Embedding
Hannah Marienwald, Jean-Baptiste Fermanian, Gilles Blanchard
We propose an improved estimator for the multi-task averaging problem, whose goal is the joint estimation of the means of multiple distributions using separate, independent data se…
Tight Bound of Incremental Cover Trees for Dynamic Diversification
Hannah Marienwald, Wikor Pronobis, Klaus-Robert Müller +1
Dynamic diversification---finding a set of data points with maximum diversity from a time-dependent sample pool---is an important task in recommender systems, web search, database…