3 papers
cs.LG2026
In-Context Multiple Instance Learning
Alexander Möllers, Marvin Sextro, Julius Hense +2
Multiple Instance Learning (MIL) addresses problems where supervision is available at the level of bags of instances and has been successfully applied in fields ranging from comput…
cs.LG2026
MapPFN: Learning Causal Perturbation Maps in Context
Marvin Sextro, Weronika KÅos, Gabriel Dernbach
Planning effective interventions in biological systems requires treatment-effect models that adapt to unseen biological contexts by identifying their specific underlying mechanisms…
cs.CV2024
xCG: Explainable Cell Graphs for Survival Prediction in Non-Small Cell Lung Cancer
Marvin Sextro, Gabriel Dernbach, Kai Standvoss +5
Understanding how deep learning models predict oncology patient risk can provide critical insights into disease progression, support clinical decision-making, and pave the way for…