On the detection of Out-Of-Distribution samples in Multiple Instance Learning

1 code implementation • 11 Sep 2023 • Loïc Le Bescond, Maria Vakalopoulou, Stergios Christodoulidis, Fabrice André, Hugues Talbot

While significant efforts have been devoted to OOD detection in classical supervised settings, the context of weakly supervised learning, particularly the Multiple Instance Learning (MIL) framework, remains under-explored.

Multiple Instance Learning Out of Distribution (OOD) Detection +1

A biology-driven deep generative model for cell-type annotation in cytometry

1 code implementation • 11 Aug 2022 • Quentin Blampey, Nadège Bercovici, Charles-Antoine Dutertre, Isabelle Pic, Fabrice André, Joana Mourato Ribeiro, Paul-Henry Cournède

Cytometry enables precise single-cell phenotyping within heterogeneous populations.

Self-Supervised Nuclei Segmentation in Histopathological Images Using Attention

1 code implementation • 16 Jul 2020 • Mihir Sahasrabudhe, Stergios Christodoulidis, Roberto Salgado, Stefan Michiels, Sherene Loi, Fabrice André, Nikos Paragios, Maria Vakalopoulou

We show that the identification of the magnification level for tiles can generate a preliminary self-supervision signal to locate nuclei.

Segmentation